31,534 Database Developers jobs in India
Data Engineer- Lead Data Engineer
Posted 1 day ago
Job Viewed
Job Description
Role Overview
We are seeking an experienced Lead Data Engineer to join our Data Engineering team at Paytm, India's leading digital payments and financial services platform. This is a critical role responsible for designing, building, and maintaining large-scale, real-time data streams that process billions of transactions and user interactions daily. Data accuracy and stream reliability are essential to our operations, as data quality issues can result in financial losses and impact customer
a Lead Data Engineer at Paytm, you will be responsible for building robust data systems that support India's largest digital payments ecosystem. You'll architect and implement reliable, real-time data streaming solutions where precision and data correctness are fundamental requirements. Your work will directly support millions of users across merchant payments, peer-to-peer transfers, bill payments, and financial services, where data accuracy is crucial for maintaining customer confidence and operational excellence.
This role requires expertise in designing fault-tolerant, scalable data architectures that maintain high uptime standards while processing peak transaction loads during festivals and high-traffic events. We place the highest priority on data quality and system reliability, as our customers depend on accurate, timely information for their financial decisions. You'll collaborate with cross-functional teams including data scientists, product managers, and risk engineers to deliver data solutions that enable real-time fraud detection, personalized recommendations, credit scoring, and regulatory compliance reporting.
Key technical challenges include maintaining data consistency across distributed systems with demanding performance requirements, implementing comprehensive data quality frameworks with real-time validation, optimizing query performance on large datasets, and ensuring complete data lineage and governance across multiple business domains. At Paytm, reliable data streams are fundamental to our operations and our commitment to protecting customers' financial security and maintaining India's digital payments
Responsibilities
Data Stream Architecture & DevelopmentDesign and implement reliable, scalable data streams handling high-volume transaction data with strong data integrity controlsBuild real-time processing systems using modern data engineering frameworks (Java/Python stack) with excellent performance characteristicsDevelop robust data ingestion systems from multiple sources with built-in redundancy and monitoring capabilitiesImplement comprehensive data quality frameworks, ensuring the 4 C's: Completeness, Consistency, Conformity, and Correctness - ensuring data reliability that supports sound business decisionsDesign automated data validation, profiling, and quality monitoring systems with proactive alerting capabilitiesInfrastructure & Platform ManagementManage and optimize distributed data processing platforms with high availability requirements to ensure consistent service deliveryDesign data lake and data warehouse architectures with appropriate partitioning and indexing strategies for optimal query performanceImplement CI/CD processes for data engineering workflows with comprehensive testing and reliable deployment proceduresEnsure high availability and disaster recovery for critical data systems to maintain business continuity
Performance & OptimizationMonitor and optimize streaming performance with focus on latency reduction and operational efficiencyImplement efficient data storage strategies including compression, partitioning, and lifecycle management with cost considerationsTroubleshoot and resolve complex data streaming issues in production environments with effective response protocolsConduct proactive capacity planning and performance tuning to support business growth and data volume increases
Collaboration & Leadership Work closely with data scientists, analysts, and product teams to understand important data requirements and service level expectationsMentor junior data engineers with emphasis on data quality best practices and customer-focused approachParticipate in architectural reviews and help establish data engineering standards that prioritize reliability and accuracyDocument technical designs, processes, and operational procedures with focus on maintainability and knowledge sharing
Required Qualifications
Experience & EducationBachelor's or Master's degree in Computer Science, Engineering, or related technical field
7+ years (Senior) of hands-on data engineering experience
Proven experience with large-scale data processing systems (preferably in fintech/payments domain)
Experience building and maintaining production data streams processing TB/PB scale data with strong performance and reliability standards
Technical Skills & RequirementsProgramming Languages:
Expert-level proficiency in both Python and Java; experience with Scala preferred
Big Data Technologies: Apache Spark (PySpark, Spark SQL, Spark with Java), Apache Kafka, Apache Airflow
Cloud Platforms: AWS (EMR, Glue, Redshift, S3, Lambda) or equivalent Azure/GCP services
Databases: Strong SQL skills, experience with both relational (PostgreSQL, MySQL) and NoSQL databases (MongoDB, Cassandra, Redis)
Data Quality Management: Deep understanding of the 4 C's framework - Completeness, Consistency, Conformity, and Correctness
Data Governance: Experience with data lineage tracking, metadata management, and data cataloging
Data Formats & Protocols: Parquet, Avro, JSON, REST APIs, GraphQLContainerization & DevOps: Docker, Kubernetes, Git, GitLab/GitHub with CI/CD pipeline experience
Monitoring & Observability: Experience with Prometheus, Grafana, or similar monitoring tools
Data Modeling: Dimensional modeling, data vault, or similar methodologies
Streaming Technologies: Apache Flink, Kinesis, or Pulsar experience is a plus
Infrastructure as Code: Terraform, CloudFormation (preferred)
Java-specific: Spring Boot, Maven/Gradle, JUnit for building robust data services
Preferred Qualifications
Domain Expertise
Previous experience in fintech, payments, or banking industry with solid understanding of regulatory compliance and financial data requirementsUnderstanding of financial data standards, PCI DSS compliance, and data privacy regulations where compliance is essential for business operationsExperience with real-time fraud detection or risk management systems where data accuracy is crucial for customer protection
Advanced Technical Skills (Preferred)
Experience building automated data quality frameworks covering all 4 C's dimensionsKnowledge of machine learning stream orchestration (MLflow, Kubeflow)Familiarity with data mesh or federated data architecture patternsExperience with change data capture (CDC) tools and techniques
Leadership & Soft SkillsStrong problem-solving abilities with experience debugging complex distributed systems in production environmentsExcellent communication skills with ability to explain technical concepts to diverse stakeholders while highlighting business valueExperience mentoring team members and leading technical initiatives with focus on building a quality-oriented cultureProven track record of delivering projects successfully in dynamic, fast-paced financial technology environments
Data Engineer- Senior Data Engineer
Posted 1 day ago
Job Viewed
Job Description
The Role
We're looking for a senior AI engineer who can build production-grade agentic AI systems. You'll be working at the intersection of cutting-edge AI research and scalable engineering, creating autonomous agents that can reason, plan, and execute complex tasks reliably at scale.
What We Need
Agentic AI & LLM Engineering
You should have hands-on experience with:
Multi-agent systems: Building agents that coordinate, communicate, and work together on complex workflows
Agent orchestration: Designing systems where AI agents can plan multi-step tasks, use tools, and make autonomous decisions
LLMOps Experience: End-to-End LLM Lifecycle Management - hands-on experience managing the complete LLM workflow from prompt engineering and dataset curation through model fine-tuning, evaluation, and deployment. This includes versioning prompts, managing training datasets, orchestrating distributed training jobs, and implementing automated model validation pipelines. Production LLM Infrastructure - experience building and maintaining production LLM serving infrastructure including model registries, A/B testing frameworks for comparing model versions, automated rollback mechanisms, and monitoring systems that track model performance, latency, and cost metrics in real-time.
AI Observability: Experience implementing comprehensive monitoring and tracing for AI systems, including prompt tracking, model output analysis, cost monitoring, and agent decision-making visibility across complex workflows.
Evaluation frameworks: Creating comprehensive testing for agent performance, safety, and goal achievement
LLM inference optimization: Scaling model serving with techniques like batching, caching, and efficient frameworks (vLLM, TensorRT-LLM)
Systems Engineering
Strong backend development skills including:
Python expertise: FastAPI, Django, or Flask for building robust APIs that handle agent workflows
Distributed systems: Microservices, event-driven architectures, and message queues (Kafka, RabbitMQ) for agent coordination
Database strategy: Vector databases, traditional SQL/NoSQL, and caching layers optimized for agent state management
Web-scale design: Systems handling millions of requests with proper load balancing and fault tolerance
DevOps (Non-negotiable)
Kubernetes: Working knowledge required - deployments, services, cluster management
Containerization: Docker with production optimization and security best practices
CI/CD: Automated testing and deployment pipelines
Infrastructure as Code: Terraform, Helm charts
Monitoring: Prometheus, Grafana for tracking complex agent behaviors
Programing Language : Java , Python
What You'll Build
You'll architect the infrastructure that powers our autonomous AI systems:
Agent Orchestration Platform: Multi-agent coordination systems that handle complex, long-running workflows with proper state management and failure recovery.
Evaluation Infrastructure: Comprehensive frameworks that assess agent performance across goal achievement, efficiency, safety, and decision-making quality.
Production AI Services: High-throughput systems serving millions of users with intelligent resource management and robust fallback mechanisms.
Training Systems: Scalable pipelines for SFT and DPO that continuously improve agent capabilities based on real-world performance and human feedback.
Who You Are
You've spent serious time in production environments building AI systems that actually work. You understand the unique challenges of agentic AI - managing state across long conversations, handling partial failures in multi-step processes, and ensuring agents stay aligned with their intended goals.
You've dealt with the reality that the hardest problems aren't always algorithmic. Sometimes it's about making an agent retry gracefully when an API call fails, or designing an observability layer that catches when an agent starts behaving unexpectedly, or building systems that can scale from handling dozens of agent interactions to millions.
You're excited about the potential of AI agents but pragmatic about the engineering work required to make them reliable in production.
Data Engineer- Lead Data Engineer
Posted today
Job Viewed
Job Description
Role Overview
We are seeking an experienced Lead Data Engineer to join our Data Engineering team at Paytm, India's leading digital payments and financial services platform. This is a critical role responsible for designing, building, and maintaining large-scale, real-time data streams that process billions of transactions and user interactions daily. Data accuracy and stream reliability are essential to our operations, as data quality issues can result in financial losses and impact customer trust.
As a Lead Data Engineer at Paytm, you will be responsible for building robust data systems that support India's largest digital payments ecosystem. You'll architect and implement reliable, real-time data streaming solutions where precision and data correctness are fundamental requirements . Your work will directly support millions of users across merchant payments, peer-to-peer transfers, bill payments, and financial services, where data accuracy is crucial for maintaining customer confidence and operational excellence.
This role requires expertise in designing fault-tolerant, scalable data architectures that maintain high uptime standards while processing peak transaction loads during festivals and high-traffic events. We place the highest priority on data quality and system reliability, as our customers depend on accurate, timely information for their financial decisions. You'll collaborate with cross-functional teams including data scientists, product managers, and risk engineers to deliver data solutions that enable real-time fraud detection, personalized recommendations, credit scoring, and regulatory compliance reporting.
Key technical challenges include maintaining data consistency across distributed systems with demanding performance requirements, implementing comprehensive data quality frameworks with real-time validation, optimizing query performance on large datasets, and ensuring complete data lineage and governance across multiple business domains. At Paytm, reliable data streams are fundamental to our operations and our commitment to protecting customers' financial security and maintaining India's digital payments infrastructure.
Key Responsibilities
Data Stream Architecture & Development Design and implement reliable, scalable data streams handling high-volume transaction data with strong data integrity controlsBuild real-time processing systems using modern data engineering frameworks (Java/Python stack) with excellent performance characteristicsDevelop robust data ingestion systems from multiple sources with built-in redundancy and monitoring capabilitiesImplement comprehensive data quality frameworks, ensuring the 4 C's: Completeness, Consistency, Conformity, and Correctness - ensuring data reliability that supports sound business decisionsDesign automated data validation, profiling, and quality monitoring systems with proactive alerting capabilities Infrastructure & Platform Management Manage and optimize distributed data processing platforms with high availability requirements to ensure consistent service deliveryDesign data lake and data warehouse architectures with appropriate partitioning and indexing strategies for optimal query performanceImplement CI/CD processes for data engineering workflows with comprehensive testing and reliable deployment proceduresEnsure high availability and disaster recovery for critical data systems to maintain business continuity
Performance & Optimization Monitor and optimize streaming performance with focus on latency reduction and operational efficiencyImplement efficient data storage strategies including compression, partitioning, and lifecycle management with cost considerationsTroubleshoot and resolve complex data streaming issues in production environments with effective response protocolsConduct proactive capacity planning and performance tuning to support business growth and data volume increases
Collaboration & Leadership Work closely with data scientists, analysts, and product teams to understand important data requirements and service level expectationsMentor junior data engineers with emphasis on data quality best practices and customer-focused approachParticipate in architectural reviews and help establish data engineering standards that prioritize reliability and accuracyDocument technical designs, processes, and operational procedures with focus on maintainability and knowledge sharing
Required Qualifications
Experience & Education Bachelor's or Master's degree in Computer Science, Engineering, or related technical field
7+ years (Senior) of hands-on data engineering experience
Proven experience with large-scale data processing systems (preferably in fintech/payments domain)
Experience building and maintaining production data streams processing TB/PB scale data with strong performance and reliability standards
Technical Skills & RequirementsProgramming Languages:
Expert-level proficiency in both Python and Java; experience with Scala preferred
Big Data Technologies: Apache Spark (PySpark, Spark SQL, Spark with Java), Apache Kafka, Apache Airflow
Cloud Platforms: AWS (EMR, Glue, Redshift, S3, Lambda) or equivalent Azure/GCP services
Databases: Strong SQL skills, experience with both relational (PostgreSQL, MySQL) and NoSQL databases (MongoDB, Cassandra, Redis)
Data Quality Management: Deep understanding of the 4 C's framework - Completeness, Consistency, Conformity, and Correctness
Data Governance: Experience with data lineage tracking, metadata management, and data cataloging
Data Formats & Protocols: Parquet, Avro, JSON, REST APIs, GraphQL Containerization & DevOps: Docker, Kubernetes, Git, GitLab/GitHub with CI/CD pipeline experience
Monitoring & Observability: Experience with Prometheus, Grafana, or similar monitoring tools
Data Modeling: Dimensional modeling, data vault, or similar methodologies
Streaming Technologies: Apache Flink, Kinesis, or Pulsar experience is a plus
Infrastructure as Code: Terraform, CloudFormation (preferred)
Java-specific: Spring Boot, Maven/Gradle, JUnit for building robust data services
Preferred Qualifications
Domain Expertise
Previous experience in fintech, payments, or banking industry with solid understanding of regulatory compliance and financial data requirementsUnderstanding of financial data standards, PCI DSS compliance, and data privacy regulations where compliance is essential for business operationsExperience with real-time fraud detection or risk management systems where data accuracy is crucial for customer protection
Advanced Technical Skills (Preferred)
Experience building automated data quality frameworks covering all 4 C's dimensionsKnowledge of machine learning stream orchestration (MLflow, Kubeflow)Familiarity with data mesh or federated data architecture patternsExperience with change data capture (CDC) tools and techniques
Leadership & Soft Skills Strong problem-solving abilities with experience debugging complex distributed systems in production environmentsExcellent communication skills with ability to explain technical concepts to diverse stakeholders while highlighting business valueExperience mentoring team members and leading technical initiatives with focus on building a quality-oriented cultureProven track record of delivering projects successfully in dynamic, fast-paced financial technology environments
What We Offer
Opportunity to work with cutting-edge technology at scaleCompetitive salary and equity compensation
Comprehensive health and wellness benefits
Professional development opportunities and conference attendanceFlexible working arrangements
Chance to impact millions of users across India's digital payments ecosystem
Application Process
Interested candidates should submit:
Updated resume highlighting relevant data engineering experience with emphasis on real-time systems and data quality
Portfolio or GitHub profile showcasing data engineering projects, particularly those involving high-throughput streaming systems
Cover letter explaining interest in fintech/payments domain and understanding of data criticality in financial services
References from previous technical managers or senior colleagues who can attest to your data quality standards
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Data Engineer / Senior Data Engineer
Posted today
Job Viewed
Job Description
Are you excited by the prospect of wrangling data, helping develop information systems/sources/tools, and shaping the way businesses make decisions? The Go-To-Markets Data Analytics team is looking for a skilled Data Engineer / Senior Data Engineer who is motivated to deliver top notch data-engineering solutions to support business intelligence, data science, and self-service data solutions.
About the Role:
In this role as a Data Engineer / Senior Data Engineer, you will:
Design, develop, optimize, and automate data pipelines that blend and transform data across different sources to help drive business intelligence, data science, and self-service data solutions.
Work closely with data scientists and data visualization teams to understand data requirements to ensure the availability of high-quality data for analytics, modelling, and reporting.
Build pipelines that source, transform, and load data that’s both structured and unstructured keeping in mind data security and access controls.
Explore large volumes of data with curiosity and conviction.
Contribute to the strategy and architecture of data management systems and solutions.
Proactively troubleshoot and resolve data-related and performance bottlenecks in a timely manner.
Be open to learning and working on emerging technologies in the data engineering, data science and cloud computing space.
Have the curiosity to interrogate data, conduct independent research, utilize various techniques, and tackle ambiguous problems.
Shift Timings: 12 PM to 9 PM (IST)
Work from office for 2 days in a week (Mandatory)
About You
You’re a fit for the role of Data Engineer, if your background includes:
Must have at least 4+ years of total work experience with at least 2+ years in data engineering or analytics domains.
Graduates in data analytics, data science, computer science, software engineering or other data centric disciplines.
SQL Proficiency a must.
Experience with data pipeline and transformation tools such as dbt, Glue, FiveTran, Alteryx or similar solutions.
Experience using cloud-based data warehouse solutions such as Snowflake, Redshift, Azure.
Experience with orchestration tools like Airflow or Dagster.
Preferred experience using Amazon Web Services (S3, Glue, Athena, Quick sight).
Data modelling knowledge of various schemas like snowflake and star.
Has built data pipelines and other custom automated solutions to speed the ingestion, analysis, and visualization of large volumes of data.
Knowledge building ETL workflows, database design, and query optimization.
Has experience of a scripting language like Python.
Works well within a team and collaborates with colleagues across domains and geographies.
Excellent oral, written, and visual communication skills.
Has a demonstrable ability to assimilate new information thoroughly and quickly.
Strong logical and scientific approach to problem-solving.
Can articulate complex results in a simple and concise manner to all levels within the organization.
#LI-GS2
What’s in it For You?
Hybrid Work Model: We’ve adopted a flexible hybrid working environment (2-3 days a week in the office depending on the role) for our office-based roles while delivering a seamless experience that is digitally and physically connected.
Flexibility & Work-Life Balance: Flex My Way is a set of supportive workplace policies designed to help manage personal and professional responsibilities, whether caring for family, giving back to the community, or finding time to refresh and reset. This builds upon our flexible work arrangements, including work from anywhere for up to 8 weeks per year, empowering employees to achieve a better work-life balance.
Career Development and Growth: By fostering a culture of continuous learning and skill development, we prepare our talent to tackle tomorrow’s challenges and deliver real-world solutions. Our Grow My Way programming and skills-first approach ensures you have the tools and knowledge to grow, lead, and thrive in an AI-enabled future.
Industry Competitive Benefits: We offer comprehensive benefit plans to include flexible vacation, two company-wide Mental Health Days off, access to the Headspace app, retirement savings, tuition reimbursement, employee incentive programs, and resources for mental, physical, and financial wellbeing.
Culture: Globally recognized, award-winning reputation for inclusion and belonging, flexibility, work-life balance, and more. We live by our values: Obsess over our Customers, Compete to Win, Challenge (Y)our Thinking, Act Fast / Learn Fast, and Stronger Together.
Social Impact: Make an impact in your community with our Social Impact Institute. We offer employees two paid volunteer days off annually and opportunities to get involved with pro-bono consulting projects and Environmental, Social, and Governance (ESG) initiatives.
Making a Real-World Impact: We are one of the few companies globally that helps its customers pursue justice, truth, and transparency. Together, with the professionals and institutions we serve, we help uphold the rule of law, turn the wheels of commerce, catch bad actors, report the facts, and provide trusted, unbiased information to people all over the world.
About Us
Thomson Reuters informs the way forward by bringing together the trusted content and technology that people and organizations need to make the right decisions. We serve professionals across legal, tax, accounting, compliance, government, and media. Our products combine highly specialized software and insights to empower professionals with the data, intelligence, and solutions needed to make informed decisions, and to help institutions in their pursuit of justice, truth, and transparency. Reuters, part of Thomson Reuters, is a world leading provider of trusted journalism and news.
We are powered by the talents of 26,000 employees across more than 70 countries, where everyone has a chance to contribute and grow professionally in flexible work environments. At a time when objectivity, accuracy, fairness, and transparency are under attack, we consider it our duty to pursue them. Sound exciting? Join us and help shape the industries that move society forward.
As a global business, we rely on the unique backgrounds, perspectives, and experiences of all employees to deliver on our business goals. To ensure we can do that, we seek talented, qualified employees in all our operations around the world regardless of race, color, sex/gender, including pregnancy, gender identity and expression, national origin, religion, sexual orientation, disability, age, marital status, citizen status, veteran status, or any other protected classification under applicable law. Thomson Reuters is proud to be an Equal Employment Opportunity Employer providing a drug-free workplace.
We also make reasonable accommodations for qualified individuals with disabilities and for sincerely held religious beliefs in accordance with applicable law. More information on requesting an accommodation .
Learn more on how to protect yourself from fraudulent job postings .
More information about Thomson Reuters can be found on
Data Engineer / Senior Data Engineer
Posted today
Job Viewed
Job Description
Are you excited by the prospect of wrangling data, helping develop information systems/sources/tools, and shaping the way businesses make decisions? The Go-To-Markets Data Analytics team is looking for a skilled Data Engineer / Senior Data Engineer who is motivated to deliver top notch data-engineering solutions to support business intelligence, data science, and self-service data solutions.
About the Role:
In this role as a Data Engineer / Senior Data Engineer, you will:
Design, develop, optimize, and automate data pipelines that blend and transform data across different sources to help drive business intelligence, data science, and self-service data solutions.
Work closely with data scientists and data visualization teams to understand data requirements to ensure the availability of high-quality data for analytics, modelling, and reporting.
Build pipelines that source, transform, and load data that’s both structured and unstructured keeping in mind data security and access controls.
Explore large volumes of data with curiosity and conviction.
Contribute to the strategy and architecture of data management systems and solutions.
Proactively troubleshoot and resolve data-related and performance bottlenecks in a timely manner.
Be open to learning and working on emerging technologies in the data engineering, data science and cloud computing space.
Have the curiosity to interrogate data, conduct independent research, utilize various techniques, and tackle ambiguous problems.
Shift Timings: 12 PM to 9 PM (IST)
Work from office for 2 days in a week (Mandatory)
About You
You’re a fit for the role of Data Engineer, if your background includes:
Must have at least 4+ years of total work experience with at least 2+ years in data engineering or analytics domains.
Graduates in data analytics, data science, computer science, software engineering or other data centric disciplines.
SQL Proficiency a must.
Experience with data pipeline and transformation tools such as dbt, Glue, FiveTran, Alteryx or similar solutions.
Experience using cloud-based data warehouse solutions such as Snowflake, Redshift, Azure.
Experience with orchestration tools like Airflow or Dagster.
Preferred experience using Amazon Web Services (S3, Glue, Athena, Quick sight).
Data modelling knowledge of various schemas like snowflake and star.
Has built data pipelines and other custom automated solutions to speed the ingestion, analysis, and visualization of large volumes of data.
Knowledge building ETL workflows, database design, and query optimization.
Has experience of a scripting language like Python.
Works well within a team and collaborates with colleagues across domains and geographies.
Excellent oral, written, and visual communication skills.
Has a demonstrable ability to assimilate new information thoroughly and quickly.
Strong logical and scientific approach to problem-solving.
Can articulate complex results in a simple and concise manner to all levels within the organization.
#LI-GS2
What’s in it For You?
Hybrid Work Model: We’ve adopted a flexible hybrid working environment (2-3 days a week in the office depending on the role) for our office-based roles while delivering a seamless experience that is digitally and physically connected.
Flexibility & Work-Life Balance: Flex My Way is a set of supportive workplace policies designed to help manage personal and professional responsibilities, whether caring for family, giving back to the community, or finding time to refresh and reset. This builds upon our flexible work arrangements, including work from anywhere for up to 8 weeks per year, empowering employees to achieve a better work-life balance.
Career Development and Growth: By fostering a culture of continuous learning and skill development, we prepare our talent to tackle tomorrow’s challenges and deliver real-world solutions. Our Grow My Way programming and skills-first approach ensures you have the tools and knowledge to grow, lead, and thrive in an AI-enabled future.
Industry Competitive Benefits: We offer comprehensive benefit plans to include flexible vacation, two company-wide Mental Health Days off, access to the Headspace app, retirement savings, tuition reimbursement, employee incentive programs, and resources for mental, physical, and financial wellbeing.
Culture: Globally recognized, award-winning reputation for inclusion and belonging, flexibility, work-life balance, and more. We live by our values: Obsess over our Customers, Compete to Win, Challenge (Y)our Thinking, Act Fast / Learn Fast, and Stronger Together.
Social Impact: Make an impact in your community with our Social Impact Institute. We offer employees two paid volunteer days off annually and opportunities to get involved with pro-bono consulting projects and Environmental, Social, and Governance (ESG) initiatives.
Making a Real-World Impact: We are one of the few companies globally that helps its customers pursue justice, truth, and transparency. Together, with the professionals and institutions we serve, we help uphold the rule of law, turn the wheels of commerce, catch bad actors, report the facts, and provide trusted, unbiased information to people all over the world.
About Us
Thomson Reuters informs the way forward by bringing together the trusted content and technology that people and organizations need to make the right decisions. We serve professionals across legal, tax, accounting, compliance, government, and media. Our products combine highly specialized software and insights to empower professionals with the data, intelligence, and solutions needed to make informed decisions, and to help institutions in their pursuit of justice, truth, and transparency. Reuters, part of Thomson Reuters, is a world leading provider of trusted journalism and news.
We are powered by the talents of 26,000 employees across more than 70 countries, where everyone has a chance to contribute and grow professionally in flexible work environments. At a time when objectivity, accuracy, fairness, and transparency are under attack, we consider it our duty to pursue them. Sound exciting? Join us and help shape the industries that move society forward.
As a global business, we rely on the unique backgrounds, perspectives, and experiences of all employees to deliver on our business goals. To ensure we can do that, we seek talented, qualified employees in all our operations around the world regardless of race, color, sex/gender, including pregnancy, gender identity and expression, national origin, religion, sexual orientation, disability, age, marital status, citizen status, veteran status, or any other protected classification under applicable law. Thomson Reuters is proud to be an Equal Employment Opportunity Employer providing a drug-free workplace.
We also make reasonable accommodations for qualified individuals with disabilities and for sincerely held religious beliefs in accordance with applicable law. More information on requesting an accommodation .
Learn more on how to protect yourself from fraudulent job postings .
More information about Thomson Reuters can be found on
Senior Data Engineer / Data Engineer
Posted today
Job Viewed
Job Description
Desired Experience: 3-8 years
Salary: Best-in-industry
Location: Gurgaon ( 5 days onsite)
Overview:
You will act as a key member of the Data consulting team, working directly with the partners and senior stakeholders of the clients designing and implementing big data and analytics solutions. Communication and organisation skills are keys for this position, along with a problem-solution attitude.
What is in it for you:
Opportunity to work with a world class team of business consultants and engineers solving some of the most complex business problems by applying data and analytics techniques
Fast track career growth in a highly entrepreneurial work environment
Best-in-industry renumeration package
Essential Technical Skills:
Technical expertise with emerging Big Data technologies, such as: Python, Spark, Hadoop, Clojure, Git, SQL and Databricks; and visualization tools: Tableau and PowerBI
Experience with cloud, container and micro service infrastructures
Experience working with divergent data sets that meet the requirements of the Data Science and Data Analytics teams
Hands-on experience with data modelling, query techniques and complexity analysis
Desirable Skills:
Experience/Knowledge of working in an agile environment and experience with agile methodologies such as Scrum
Experience of working with development teams and product owners to understand their requirement
Certifications on any of the above areas will be preferred.
Your duties will include:
Develop data solutions within a Big Data Azure and/or other cloud environments
Working with divergent data sets that meet the requirements of the Data Science and Data Analytics teams
Build and design Data Architectures using Azure Data factory, Databricks, Data lake, Synapse
Liaising with CTO, Product Owners and other Operations teams to deliver engineering roadmaps showing key items such as upgrades, technical refreshes and new versions
Perform data mapping activities to describe source data, target data and the high-level or detailed transformations that need to occur;
Assist Data Analyst team in developing KPIs and reporting in tools viz. Power BI, Tableau
Data Integration, Transformation, Modelling
Maintaining all relevant documentation and knowledge bases
Research and suggest new database products, services and protocols
Essential Personal Traits:
You should be able to work independently and communicate effectively with remote teams.
Timely communication/escalation of issues/dependencies to higher management.
Curiosity to learn and apply emerging technologies to solve business problems
** Interested candidate please send thier resume on - and **
Senior Data Engineer / Data Engineer
Posted today
Job Viewed
Job Description
LOOKING FOR IMMEDIATE JOINERS OR 15 DAYS NOTICE PERIODS AND THIS IS WORK FROM HOME OPPORTUNITY
Position: Senior Data Engineer / Data Engineer
Desired Experience: 3-8 years
Salary: Best-in-industry
You will act as a key member of the Data consulting team, working directly with the partners and senior
stakeholders of the clients designing and implementing big data and analytics solutions. Communication
and organisation skills are keys for this position, along with a problem-solution attitude.
What is in it for you:
Opportunity to work with a world class team of business consultants and engineers solving some of
the most complex business problems by applying data and analytics techniques
Fast track career growth in a highly entrepreneurial work environment
Best-in-industry renumeration package
Essential Technical Skills:
Technical expertise with emerging Big Data technologies, such as: Python, Spark, Hadoop, Clojure,
Git, SQL and Databricks; and visualization tools: Tableau and PowerBI
Experience with cloud, container and micro service infrastructures
Experience working with divergent data sets that meet the requirements of the Data Science and
Data Analytics teams
Hands-on experience with data modelling, query techniques and complexity analysis
Desirable Skills:
Experience/Knowledge of working in an agile environment and experience with agile
methodologies such as Scrum
Experience of working with development teams and product owners to understand their
requirement
Certifications on any of the above areas will be preferred.
Your duties will include:
Develop data solutions within a Big Data Azure and/or other cloud environments
Working with divergent data sets that meet the requirements of the Data Science and Data Analytics
teams
Build and design Data Architectures using Azure Data factory, Databricks, Data lake, Synapse
Liaising with CTO, Product Owners and other Operations teams to deliver engineering roadmaps
showing key items such as upgrades, technical refreshes and new versions
Perform data mapping activities to describe source data, target data and the high-level or
detailed transformations that need to occur;
Assist Data Analyst team in developing KPIs and reporting in tools viz. Power BI, Tableau
Data Integration, Transformation, Modelling
Maintaining all relevant documentation and knowledge bases
Research and suggest new database products, services and protocols
Essential Personal Traits:
You should be able to work independently and communicate effectively with remote teams.
Timely communication/escalation of issues/dependencies to higher management.
Curiosity to learn and apply emerging technologies to solve business problems
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Data Engineer- Senior Data Engineer
Posted today
Job Viewed
Job Description
Data Engineer- Senior Data Engineer
Posted today
Job Viewed
Job Description
The Role
We're looking for a senior AI engineer who can build production-grade agentic AI systems. You'll be working at the intersection of cutting-edge AI research and scalable engineering, creating autonomous agents that can reason, plan, and execute complex tasks reliably at scale.
What We Need
Agentic AI & LLM Engineering
You should have hands-on experience with:
Multi-agent systems : Building agents that coordinate, communicate, and work together on complex workflows
Agent orchestration : Designing systems where AI agents can plan multi-step tasks, use tools, and make autonomous decisions
LLMOps Experience : End-to-End LLM Lifecycle Management - hands-on experience managing the complete LLM workflow from prompt engineering and dataset curation through model fine-tuning, evaluation, and deployment. This includes versioning prompts, managing training datasets, orchestrating distributed training jobs, and implementing automated model validation pipelines. Production LLM Infrastructure - experience building and maintaining production LLM serving infrastructure including model registries, A/B testing frameworks for comparing model versions, automated rollback mechanisms, and monitoring systems that track model performance, latency, and cost metrics in real-time.
AI Observability : Experience implementing comprehensive monitoring and tracing for AI systems, including prompt tracking, model output analysis, cost monitoring, and agent decision-making visibility across complex workflows.
Evaluation frameworks : Creating comprehensive testing for agent performance, safety, and goal achievement
LLM inference optimization : Scaling model serving with techniques like batching, caching, and efficient frameworks (vLLM, TensorRT-LLM)
Systems Engineering
Strong backend development skills including:
Python expertise : FastAPI, Django, or Flask for building robust APIs that handle agent workflows
Distributed systems : Microservices, event-driven architectures, and message queues (Kafka, RabbitMQ) for agent coordination
Database strategy : Vector databases, traditional SQL/NoSQL, and caching layers optimized for agent state management
Web-scale design : Systems handling millions of requests with proper load balancing and fault tolerance
DevOps (Non-negotiable)
Kubernetes : Working knowledge required - deployments, services, cluster management
Containerization : Docker with production optimization and security best practices
CI/CD : Automated testing and deployment pipelines
Infrastructure as Code : Terraform, Helm charts
Monitoring : Prometheus, Grafana for tracking complex agent behaviors
Programing Language : Java , Python
What You'll Build
You'll architect the infrastructure that powers our autonomous AI systems:
Agent Orchestration Platform : Multi-agent coordination systems that handle complex, long-running workflows with proper state management and failure recovery.
Evaluation Infrastructure : Comprehensive frameworks that assess agent performance across goal achievement, efficiency, safety, and decision-making quality.
Production AI Services : High-throughput systems serving millions of users with intelligent resource management and robust fallback mechanisms.
Training Systems : Scalable pipelines for SFT and DPO that continuously improve agent capabilities based on real-world performance and human feedback.
Who You Are
You've spent serious time in production environments building AI systems that actually work. You understand the unique challenges of agentic AI - managing state across long conversations, handling partial failures in multi-step processes, and ensuring agents stay aligned with their intended goals.
You've dealt with the reality that the hardest problems aren't always algorithmic. Sometimes it's about making an agent retry gracefully when an API call fails, or designing an observability layer that catches when an agent starts behaving unexpectedly, or building systems that can scale from handling dozens of agent interactions to millions.
You're excited about the potential of AI agents but pragmatic about the engineering work required to make them reliable in production.
PI503be25532c
Data Engineer
Posted 4 days ago
Job Viewed
Job Description
**Note:- Although the role category specified in the GPP is Remote, the requirement is for Hybrid working model from Cummins Pune Office.**
**Job Summary:**
Supports, develops and maintains a data and analytics platform. Effectively and efficiently process, store and make data available to analysts and other consumers. Works with the Business and IT teams to understand the requirements to best leverage the technologies to enable agile data delivery at scale.
**Key Responsibilities:**
Implements and automates deployment of our distributed system for ingesting and transforming data from various types of sources (relational, event-based, unstructured). Implements methods to continuously monitor and troubleshoot data quality and data integrity issues. Implements data governance processes and methods for managing metadata, access, retention to data for internal and external users. Develops reliable, efficient, scalable and quality data pipelines with monitoring and alert mechanisms that combine a variety of sources using ETL/ELT tools or scripting languages. Develops physical data models and implements data storage architectures as per design guidelines. Analyzes complex data elements and systems, data flow, dependencies, and relationships in order to contribute to conceptual physical and logical data models. Participates in testing and troubleshooting of data pipelines. Develops and operates large scale data storage and processing solutions using different distributed and cloud based platforms for storing data (e.g. Data Lakes, Hadoop, Hbase, Cassandra, MongoDB, Accumulo, DynamoDB, others). Uses agile development technologies, such as DevOps, Scrum, Kanban and continuous improvement cycle, for data driven application.
**RESPONSIBILITIES**
**Competencies:**
System Requirements Engineering - Uses appropriate methods and tools to translate stakeholder needs into verifiable requirements to which designs are developed; establishes acceptance criteria for the system of interest through analysis, allocation and negotiation; tracks the status of requirements throughout the system lifecycle; assesses the impact of changes to system requirements on project scope, schedule, and resources; creates and maintains information linkages to related artifacts.
Collaborates - Building partnerships and working collaboratively with others to meet shared objectives.
Communicates effectively - Developing and delivering multi-mode communications that convey a clear understanding of the unique needs of different audiences.
Customer focus - Building strong customer relationships and delivering customer-centric solutions.
Decision quality - Making good and timely decisions that keep the organization moving forward.
Data Extraction - Performs data extract-transform-load (ETL) activities from variety of sources and transforms them for consumption by various downstream applications and users using appropriate tools and technologies.
Programming - Creates, writes and tests computer code, test scripts, and build scripts using algorithmic analysis and design, industry standards and tools, version control, and build and test automation to meet business, technical, security, governance and compliance requirements.
Quality Assurance Metrics - Applies the science of measurement to assess whether a solution meets its intended outcomes using the IT Operating Model (ITOM), including the SDLC standards, tools, metrics and key performance indicators, to deliver a quality product.
Solution Documentation - Documents information and solution based on knowledge gained as part of product development activities; communicates to stakeholders with the goal of enabling improved productivity and effective knowledge transfer to others who were not originally part of the initial learning.
Solution Validation Testing - Validates a configuration item change or solution using the Function's defined best practices, including the Systems Development Life Cycle (SDLC) standards, tools and metrics, to ensure that it works as designed and meets customer requirements.
Data Quality - Identifies, understands and corrects flaws in data that supports effective information governance across operational business processes and decision making.
Problem Solving - Solves problems and may mentor others on effective problem solving by using a systematic analysis process by leveraging industry standard methodologies to create problem traceability and protect the customer; determines the assignable cause; implements robust, data-based solutions; identifies the systemic root causes and ensures actions to prevent problem reoccurrence are implemented.
Values differences - Recognizing the value that different perspectives and cultures bring to an organization.
**Education, Licenses, Certifications:**
College, university, or equivalent degree in relevant technical discipline, or relevant equivalent experience required. This position may require licensing for compliance with export controls or sanctions regulations.
**Experience:**
4-5 Years of experience.
Relevant experience preferred such as working in a temporary student employment, intern, co-op, or other extracurricular team activities.
Knowledge of the latest technologies in data engineering is highly preferred and includes:
- Exposure to Big Data open source
- SPARK, Scala/Java, Map-Reduce, Hive, Hbase, and Kafka or equivalent college coursework
- SQL query language
- Clustered compute cloud-based implementation experience
- Familiarity developing applications requiring large file movement for a Cloud-based environment
- Exposure to Agile software development
- Exposure to building analytical solutions
- Exposure to IoT technology
**QUALIFICATIONS**
1) Work closely with business Product Owner to understand product vision.
2) Participate in DBU Data & Analytics Power Cells to define, develop data pipelines for efficient data transport into Cummins Digital Core ( Azure DataLake, Snowflake).
3) Collaborate closely with AAI Digital Core and AAI Solutions Architecture to ensure alignment of DBU project data pipeline design standards.
4) Work under limited supervision to design, develop, test, implement complex data pipelines from transactional systems (ERP, CRM) to Datawarehouses, DataLake.
5) Responsible for creation of DBU Data & Analytics data engineering documentation and standard operating procedures (SOP) with guidance and help from senior data engineers.
6) Take part in evaluation of new data tools, POCs with guidance and help from senior data engineers.
7) Take ownership of the developed data pipelines, providing ongoing support for enhancements and performance optimization under limited supervision.
8) Assist to resolve issues that compromise data accuracy and usability.
1. Programming Languages: Proficiency in languages such as Python, Java, and/or Scala.
2. Database Management: Intermediate level expertise in SQL and NoSQL databases.
3. Big Data Technologies: Experience with Hadoop, Spark, Kafka, and other big data frameworks.
4. Cloud Services: Experience with Azure, Databricks and AWS cloud platforms.
5. ETL Processes: Strong understanding of Extract, Transform, Load (ETL) processes.
6. API: Working knowledge of API to consume data from ERP, CRM
**Job** Systems/Information Technology
**Organization** Cummins Inc.
**Role Category** Remote
**Job Type** Exempt - Experienced
**ReqID**
**Relocation Package** Yes