69,547 Data Professionals jobs in India
Data Scientist/Data Engineer/Data Analyst
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Job Description
3 - 5 Years
1 Opening
Bangalore
Role descriptionRole Proficiency:
Independently interprets data and analyses results using statistical techniques
Outcomes:
Independently Mine and acquire data from primary and secondary sources and reorganize the data in a format that can be easily read by either a machine or a person; generating insights and helping clients make better decisions.
Develop reports and analysis that effectively communicate trends patterns and predictions using relevant data.
Utilizes historical data sets and planned changes to business models and forecast business trends
Working alongside teams within the business or the management team to establish business needs.
Creates visualizations including dashboards flowcharts and graphs to relay business concepts through visuals to colleagues and other relevant stakeholders.
Set FAST goals
Measures of Outcomes:
Schedule adherence to tasks
Quality – Errors in data interpretation and Modelling
Number of business processes changed due to vital analysis.
Number of insights generated for business decisions
Number of stakeholder appreciations/escalations
Number of customer appreciations
No: of mandatory trainings completed
Outputs Expected:
Data Mining:
- Acquiring data from various sources
Reorganizing/Filtering data:
- Consider only relevant data from the mined data and convert it into a format which is consistent and analysable.
Analysis:
- Use statistical methods to analyse data and generate useful results.
Create Data Models:
- Use data to create models that depict trends in the customer base and the consumer population as a whole
Create Reports:
- Create reports depicting the trends and behaviours from the analysed data
Document:
- Create documentation for own work as well as perform peer review of documentation of others' work
Manage knowledge:
- Consume and contribute to project related documents
share point
libraries and client universities
Status Reporting:
Report status of tasks assigned
Comply with project related reporting standards and process
Code:
- Create efficient and reusable code. Follows coding best practices.
Code Versioning:
- Organize and manage the changes and revisions to code. Use a version control tool like git
bitbucket
etc.
Quality:
- Provide quality assurance of imported data
working with quality assurance analyst if necessary.
Performance Management:
- Set FAST Goals and seek feedback from supervisor
Skill Examples:
Analytical Skills: Ability to work with large amounts of data: facts figures and number crunching.
Communication Skills: Ability to present findings or translate the data into an understandable document
Critical Thinking: Ability to look at the numbers trends and data; coming up with new conclusions based on the findings.
Attention to Detail: Making sure to be vigilant in the analysis to come with accurate conclusions.
Quantitative skills - knowledge of statistical methods and data analysis software
Presentation Skills - reports and oral presentations to senior colleagues
Mathematical skills to estimate numerical data.
Work in a team environment
Proactively ask for and offer help
Knowledge Examples:
Knowledge Examples
Proficient in mathematics and calculations.
Spreadsheet tools such as Microsoft Excel or Google Sheets
Advanced knowledge of Tableau or PowerBI
SQL
Python
DBMS
Operating Systems and software platforms
Knowledge about customer domain and also sub domain where problem is solved
Code version control e.g. git bitbucket etc
Additional Comments:
NA
SkillsData Analyst,Data Science,Team Work
About USTUST is a global digital transformation solutions provider. For more than 20 years, UST has worked side by side with the world's best companies to make a real impact through transformation. Powered by technology, inspired by people and led by purpose, UST partners with their clients from design to operation. With deep domain expertise and a future-proof philosophy, UST embeds innovation and agility into their clients' organizations. With over 30,000 employees in 30 countries, UST builds for boundless impact—touching billions of lives in the process.
Data Engineer _ Data
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Summary: The Data Engineer in the Data & AI division is responsible for designing, developing, and maintaining robust data pipelines, ensuring the efficient and secure movement, transformation, and storage of data across business systems. The ideal candidate will support analytics and AI initiatives, enabling data-driven decision-making within the organisation.
Role: Data & AI Data Engineer
Location: Bangalore
Shift timings: General Shift
Roles & Responsibilities:
- Design, develop, and maintain scalable and reliable data pipelines to support analytics, reporting, and AI-driven solutions.
- Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and deliver appropriate data solutions.
- Optimise data extraction, transformation, and loading (ETL) processes for performance, scalability, and data quality.
- Implement data models, build and maintain data warehouses and lakes, and ensure data security and compliance.
- Monitor data pipeline performance and troubleshoot issues in a timely manner.
- Document data processes, pipelines, and architecture for knowledge sharing and audit purposes.
- Stay updated with industry trends and recommend best practices in data engineering and AI integration.
Must-Have Skills:
- Demonstrated proficiency in SQL and at least one programming language (Python, Java, or Scala).
- Experience with cloud platforms such as Azure, AWS, or Google Cloud (Data Factory, Databricks, Glue, BigQuery, etc.).
- Expertise in building and managing ETL pipelines and workflows.
- Strong understanding of relational and non-relational databases.
- Knowledge of data modelling, data warehousing, and data lake architectures.
- Experience with version control systems (e.g., Git) and CI/CD principles.
- Excellent problem-solving and communication skills.
Preferred skills:
- Experience with big data frameworks (Spark, Hadoop, Kafka, etc.).
- Familiarity with containerisation and orchestration tools (Docker, Kubernetes, Airflow).
- Understanding of data privacy regulations (GDPR, etc.) and data governance practices.
- Exposure to machine learning or AI model deployment pipelines.
- P ands-on experience with reporting and visualisation tools (Power BI, Tableau, etc.).
We are Navigators in the Age of Transformation: We use sophisticated technology to transform clients into the digital age, but our top priority is our positive impact on human experience. We ease anxiety and fear around digital transformation and replace it with opportunity. Launch IT is an equal opportunity employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Launch IT is committed to creating a dynamic work environment that values diversity and inclusion, respect and integrity, customer focus, and innovation.
About Company: Launch IT India is wholly owned subsidiary of The Planet Group ; ) a US company, offers attractive compensation and work environment for the prospective employees. Launch is an entrepreneurial business and technology consultancy. We help businesses and people navigate from current state to future state. Technology, tenacity, and creativity fuel our solutions with offices in Bellevue, Sacramento, Dallas, San Francisco, Hyderabad & Washington D.C.
Data Analyst/Data Engineer
Posted today
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Job Description
Performance AssuranceNavi Mumbai
Posted On
01 Sep 2025
End Date
31 Oct 2025
Required Experience
2 - 3 Years
Basic Section
No. Of Openings
1
Designation
Data Analyst/Data Engineer
Closing Date
31 Oct 2025
Organisational
MainBU
PT
Sub BU
Performance Assurance
Country
India
Region
India 1
State
Maharashtra
City
Navi Mumbai
Working Location
Ghansoli
Client Location
NA
Skills
Skill
EXCEL ANALYTICS
DATA ANALYSIS AND COORDINATION
Highest Education
No data available
CERTIFICATION
No data available
Working Language
No data available
JOB DESCRIPTION
Advance Excel , PPT creation, Proposal creation Tracking Current Month revenue tracking with Finance Maintaining Quest Data Sharing PCW case reports to Finance and Sales with Aging Sharing Invoicing status to Finance and Sales with Aging Analysis / Dashboard creation or update Daily resource - project mapping (sync With RMG) RAS status - MM with Bench bifurcation Raising RRF as per the forecast / requirement and tracking for the same till closure Each Project - GP / OM update GP/OM consolidation for Account Updating AOP (Daily) Updating leave tracker Follow ups on the Quest allocations / PCW allocation in the Quest/PCW approval cycle Updating the Delivery team on the BU RMG updates
Data Analyst/ Data Engineer
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Job Title: Data Analyst/ Data Engineer
Experience: 4B: 5 years+ work experience
4C: 7 years+ work experience
Location: Badshahpur, Sector 69, Gurugram
Shift Timings: 6AM IST - 4PM IST
5AM IST - 3PM IST (day light saving)
Exception for critical delivery:
Shift timing 4:30AM IST - 2:30PM IST
3:30AM IST - 1:30PM IST (DLS)
Skills Required:
- Advanced SQL Knowledge, Big Query Database, Profisee
- Experience with Python & Alteryx Data Visualization
- (PBI/Looker Studio)
Roles and Responsibilities:
- Proficient In IBM Cognos TM1 in below areas.
- Support – Support the existing report and coordinate with OEM in case of any issues/bugs.
- Development resource – Creation of New Reports & changes to existing ones. Should have worked on - requirement gathering , BRD and finally developing the model and testing along with documentation.
- Analyze large data sets
- MDM management. MDM tool: Profisee.
- Manage / maintain dimensions and master data
- Data Visualization Tools: Expertise "Looker Studio"
- Other tools knowledge required: Alteryx; Python
- Data Hierarchy Management: Managing data hierarchies and data mapping.
- Business Process Knowledge: Knowledgeable in business processes, especially regarding revenue recognition rules.
- Governance: Ensuring rules and processes are followed, particularly concerning revenue allocation.
- Communication: Acting as a liaison between sales teams and management.
- Hierarchy Management: Managing data hierarchies and mapping, particularly in the sales environment.
- Data Environment Understanding: A strong understanding of the data environment, including data layers and data tables.
- Troubleshooting: Ability to troubleshoot data issues, reporting issues and identify root causes.
- Collaboration: Ability to collaborate with different teams, including sales, finance, and tech teams.
- Adapt to changing business needs and new systems. Qualifications we seek in you
- FP&A tool: TM1. Manage TM1 finance data with data warehouse
Qualifications:
Bachelor in Engineer
If interested, please share your resume to
Data Engineer- Lead Data Engineer
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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
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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 - Senior Data Engineer
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Data Engineer - Lead Data Engineer
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Senior Data Engineer / Data Engineer
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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
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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