4,019 Data Leadership jobs in India

Job Summary

Role : AWS Data Architect- Leadership

Experience : 15 - 22 Years

We are seeking a highly skilled and experienced Technical Leader for our AWS Data Engineering practice. The ideal candidate will be responsible for driving Data Engineering strategy for the practice, architecting scalable enterprise level data solutions and driving the implementation of data projects on AWS. This role requires a deep understanding of AWS services and data engineering best practices.

In this role, you will be responsible for establishing and enhancing the company's Data Engineering Services Practice. You will work closely with senior stakeholders to understand business needs and deliver technical solutions. The role is well-suited for a technically proficient individual looking to thrive in a dynamic and fast-paced environment.

Responsibilities:

Technical Leadership:

● Act as a visionary leader capable of steering, motivating, and driving exceptional performance in data engagements.

● Conduct proof-of-concept projects to explore strategic opportunities and future-oriented data processing and integration capabilities, aiming to recommend scalable, flexible, and sustainable solutions that offer a high return on investment.

● Make informed architectural decisions with the customer's needs and priorities at the forefront.

● Guide and mentor engineers, actively participating in code reviews to ensure high standards of code quality.

● Collaborate closely with the sales/pre-sales/solution team to develop proposals and strategies that align with and meet the company's performance objectives.

● Partner with the marketing team to create collateral and assist recruitment teams in identifying and attracting the right talent to expand the practice.

● Design and implement data lakes, cloud data warehouses, master data management solutions, data models, and data quality assessments as part of the data engineering scope.

● Lead the development and management of data infrastructure, including tools, dashboards, queries, reports, and scripts, ensuring automation of recurring tasks while maintaining data quality and integrity

Architecture and Design:

● Design and architect scalable and robust data solutions using AWS services.

● Ensure data architecture aligns with business requirements and best practices.

● Evaluate and select appropriate AWS services for data storage, processing, and analytics.

Project Implementation:

● Oversee the implementation of data engineering projects from inception to completion.

● Engage in strategic discussions with customers and offer thought leadership to guide their decisions.

● Ensure data quality, integrity, and security throughout the data lifecycle.

Technical Innovation:

● Stay updated with the latest trends and advancements in data engineering and AWS technologies.

● Drive continuous improvement initiatives to enhance data engineering practices and processes.

● Experiment with new tools and technologies to improve data processing efficiency and effectiveness.

What is Required:

● Bachelor's or Master's degree in Engineering or Technology (B.E. / M.E. / B.Tech / M.Tech)

● 15+ years of technical hands-on experience in Data space.

● At least 4 end-to-end implementations of large-scale data projects

● Experience working on projects across multiple geographic regions

● Extensive experience with a variety of projects, including on-premises to AWS migration,modernization, greenfield implementations and cloud-to-cloud migrations.

● Proficiency with AWS data services such as AWS Glue, Redshift, S3, Athena, EMR, Lambda, and RDS.

● Strong understanding of AWS architecture and best practices for data engineering.

● Proficiency in managing AWS IAM roles, policies, and permissions.

● Proficient in SQL and Python for data processing and transformation.

● Strong understanding of data warehousing concepts, ETL/ELT processes, and data modeling.

● Experience with data integration from various sources including batch and real-time data streams.

● Familiarity with data serialization formats such as Avro, Parquet, and ORC.

● Expertise in optimizing data pipelines and query performance.

● Experience with monitoring and troubleshooting data pipelines.

● Proficiency in performance tuning and optimization of distributed computing environments.

● Experience with data governance frameworks and practices.

● Understanding of data lifecycle management and data retention policies.

● Ability to implement and manage data quality frameworks and processes.

● Hands-on experience with big data processing frameworks like Apache Spark, Hadoop, and Kafka.

● Knowledge of stream processing technologies and frameworks.

● Experience with data visualization tools such as PowerBI or Tableau.

What’s in it for you?

The experience of working in a category defining high growth startups in the transformational AI, Decision Science and Big Data Domain.

The opportunity of getting on boarded to the phenomenal growth journey and helping the customers take the next big leap in digital transformation.

The opportunity to work with a diverse, lively and proactive group of techies who are constantly raising the bar on the art of translating mounds of data into tangible business value for clients. Flexible working options available to foster productivity and work/life balance.

Job Summary

Role : AWS Data Architect- Leadership

Experience : 15 - 22 Years

We are seeking a highly skilled and experienced Technical Leader for our AWS Data Engineering practice. The ideal candidate will be responsible for driving Data Engineering strategy for the practice, architecting scalable enterprise level data solutions and driving the implementation of data projects on AWS. This role requires a deep understanding of AWS services and data engineering best practices.

In this role, you will be responsible for establishing and enhancing the company's Data Engineering Services Practice. You will work closely with senior stakeholders to understand business needs and deliver technical solutions. The role is well-suited for a technically proficient individual looking to thrive in a dynamic and fast-paced environment.

Responsibilities:

Technical Leadership:

● Act as a visionary leader capable of steering, motivating, and driving exceptional performance in data engagements.

● Conduct proof-of-concept projects to explore strategic opportunities and future-oriented data processing and integration capabilities, aiming to recommend scalable, flexible, and sustainable solutions that offer a high return on investment.

● Make informed architectural decisions with the customer's needs and priorities at the forefront.

● Guide and mentor engineers, actively participating in code reviews to ensure high standards of code quality.

● Collaborate closely with the sales/pre-sales/solution team to develop proposals and strategies that align with and meet the company's performance objectives.

● Partner with the marketing team to create collateral and assist recruitment teams in identifying and attracting the right talent to expand the practice.

● Design and implement data lakes, cloud data warehouses, master data management solutions, data models, and data quality assessments as part of the data engineering scope.

● Lead the development and management of data infrastructure, including tools, dashboards, queries, reports, and scripts, ensuring automation of recurring tasks while maintaining data quality and integrity

Architecture and Design:

● Design and architect scalable and robust data solutions using AWS services.

● Ensure data architecture aligns with business requirements and best practices.

● Evaluate and select appropriate AWS services for data storage, processing, and analytics.

Project Implementation:

● Oversee the implementation of data engineering projects from inception to completion.

● Engage in strategic discussions with customers and offer thought leadership to guide their decisions.

● Ensure data quality, integrity, and security throughout the data lifecycle.

Technical Innovation:

● Stay updated with the latest trends and advancements in data engineering and AWS technologies.

● Drive continuous improvement initiatives to enhance data engineering practices and processes.

● Experiment with new tools and technologies to improve data processing efficiency and effectiveness.

What is Required:

● Bachelor's or Master's degree in Engineering or Technology (B.E. / M.E. / B.Tech / M.Tech)

● 15+ years of technical hands-on experience in Data space.

● At least 4 end-to-end implementations of large-scale data projects

● Experience working on projects across multiple geographic regions

● Extensive experience with a variety of projects, including on-premises to AWS migration,modernization, greenfield implementations and cloud-to-cloud migrations.

● Proficiency with AWS data services such as AWS Glue, Redshift, S3, Athena, EMR, Lambda, and RDS.

● Strong understanding of AWS architecture and best practices for data engineering.

● Proficiency in managing AWS IAM roles, policies, and permissions.

● Proficient in SQL and Python for data processing and transformation.

● Strong understanding of data warehousing concepts, ETL/ELT processes, and data modeling.

● Experience with data integration from various sources including batch and real-time data streams.

● Familiarity with data serialization formats such as Avro, Parquet, and ORC.

● Expertise in optimizing data pipelines and query performance.

● Experience with monitoring and troubleshooting data pipelines.

● Proficiency in performance tuning and optimization of distributed computing environments.

● Experience with data governance frameworks and practices.

● Understanding of data lifecycle management and data retention policies.

● Ability to implement and manage data quality frameworks and processes.

● Hands-on experience with big data processing frameworks like Apache Spark, Hadoop, and Kafka.

● Knowledge of stream processing technologies and frameworks.

● Experience with data visualization tools such as PowerBI or Tableau.

What’s in it for you?

The experience of working in a category defining high growth startups in the transformational AI, Decision Science and Big Data Domain.

The opportunity of getting on boarded to the phenomenal growth journey and helping the customers take the next big leap in digital transformation.

The opportunity to work with a diverse, lively and proactive group of techies who are constantly raising the bar on the art of translating mounds of data into tangible business value for clients. Flexible working options available to foster productivity and work/life balance.

Job Summary

Role : AWS Data Architect- Leadership

Experience : 15 - 22 Years

We are seeking a highly skilled and experienced Technical Leader for our AWS Data Engineering practice. The ideal candidate will be responsible for driving Data Engineering strategy for the practice, architecting scalable enterprise level data solutions and driving the implementation of data projects on AWS. This role requires a deep understanding of AWS services and data engineering best practices.

In this role, you will be responsible for establishing and enhancing the company's Data Engineering Services Practice. You will work closely with senior stakeholders to understand business needs and deliver technical solutions. The role is well-suited for a technically proficient individual looking to thrive in a dynamic and fast-paced environment.

Responsibilities:

Technical Leadership:

● Act as a visionary leader capable of steering, motivating, and driving exceptional performance in data engagements.

● Conduct proof-of-concept projects to explore strategic opportunities and future-oriented data processing and integration capabilities, aiming to recommend scalable, flexible, and sustainable solutions that offer a high return on investment.

● Make informed architectural decisions with the customer's needs and priorities at the forefront.

● Guide and mentor engineers, actively participating in code reviews to ensure high standards of code quality.

● Collaborate closely with the sales/pre-sales/solution team to develop proposals and strategies that align with and meet the company's performance objectives.

● Partner with the marketing team to create collateral and assist recruitment teams in identifying and attracting the right talent to expand the practice.

● Design and implement data lakes, cloud data warehouses, master data management solutions, data models, and data quality assessments as part of the data engineering scope.

● Lead the development and management of data infrastructure, including tools, dashboards, queries, reports, and scripts, ensuring automation of recurring tasks while maintaining data quality and integrity

Architecture and Design:

● Design and architect scalable and robust data solutions using AWS services.

● Ensure data architecture aligns with business requirements and best practices.

● Evaluate and select appropriate AWS services for data storage, processing, and analytics.

Project Implementation:

● Oversee the implementation of data engineering projects from inception to completion.

● Engage in strategic discussions with customers and offer thought leadership to guide their decisions.

● Ensure data quality, integrity, and security throughout the data lifecycle.

Technical Innovation:

● Stay updated with the latest trends and advancements in data engineering and AWS technologies.

● Drive continuous improvement initiatives to enhance data engineering practices and processes.

● Experiment with new tools and technologies to improve data processing efficiency and effectiveness.

What is Required:

● Bachelor's or Master's degree in Engineering or Technology (B.E. / M.E. / B.Tech / M.Tech)

● 15+ years of technical hands-on experience in Data space.

● At least 4 end-to-end implementations of large-scale data projects

● Experience working on projects across multiple geographic regions

● Extensive experience with a variety of projects, including on-premises to AWS migration,modernization, greenfield implementations and cloud-to-cloud migrations.

● Proficiency with AWS data services such as AWS Glue, Redshift, S3, Athena, EMR, Lambda, and RDS.

● Strong understanding of AWS architecture and best practices for data engineering.

● Proficiency in managing AWS IAM roles, policies, and permissions.

● Proficient in SQL and Python for data processing and transformation.

● Strong understanding of data warehousing concepts, ETL/ELT processes, and data modeling.

● Experience with data integration from various sources including batch and real-time data streams.

● Familiarity with data serialization formats such as Avro, Parquet, and ORC.

● Expertise in optimizing data pipelines and query performance.

● Experience with monitoring and troubleshooting data pipelines.

● Proficiency in performance tuning and optimization of distributed computing environments.

● Experience with data governance frameworks and practices.

● Understanding of data lifecycle management and data retention policies.

● Ability to implement and manage data quality frameworks and processes.

● Hands-on experience with big data processing frameworks like Apache Spark, Hadoop, and Kafka.

● Knowledge of stream processing technologies and frameworks.

● Experience with data visualization tools such as PowerBI or Tableau.

What’s in it for you?

The experience of working in a category defining high growth startups in the transformational AI, Decision Science and Big Data Domain.

The opportunity of getting on boarded to the phenomenal growth journey and helping the customers take the next big leap in digital transformation.

The opportunity to work with a diverse, lively and proactive group of techies who are constantly raising the bar on the art of translating mounds of data into tangible business value for clients. Flexible working options available to foster productivity and work/life balance.

Job Summary

Role : AWS Data Architect- Leadership

Experience : 15 - 22 Years

We are seeking a highly skilled and experienced Technical Leader for our AWS Data Engineering practice. The ideal candidate will be responsible for driving Data Engineering strategy for the practice, architecting scalable enterprise level data solutions and driving the implementation of data projects on AWS. This role requires a deep understanding of AWS services and data engineering best practices.

In this role, you will be responsible for establishing and enhancing the company's Data Engineering Services Practice. You will work closely with senior stakeholders to understand business needs and deliver technical solutions. The role is well-suited for a technically proficient individual looking to thrive in a dynamic and fast-paced environment.

Responsibilities:

Technical Leadership:

● Act as a visionary leader capable of steering, motivating, and driving exceptional performance in data engagements.

● Conduct proof-of-concept projects to explore strategic opportunities and future-oriented data processing and integration capabilities, aiming to recommend scalable, flexible, and sustainable solutions that offer a high return on investment.

● Make informed architectural decisions with the customer's needs and priorities at the forefront.

● Guide and mentor engineers, actively participating in code reviews to ensure high standards of code quality.

● Collaborate closely with the sales/pre-sales/solution team to develop proposals and strategies that align with and meet the company's performance objectives.

● Partner with the marketing team to create collateral and assist recruitment teams in identifying and attracting the right talent to expand the practice.

● Design and implement data lakes, cloud data warehouses, master data management solutions, data models, and data quality assessments as part of the data engineering scope.

● Lead the development and management of data infrastructure, including tools, dashboards, queries, reports, and scripts, ensuring automation of recurring tasks while maintaining data quality and integrity

Architecture and Design:

● Design and architect scalable and robust data solutions using AWS services.

● Ensure data architecture aligns with business requirements and best practices.

● Evaluate and select appropriate AWS services for data storage, processing, and analytics.

Project Implementation:

● Oversee the implementation of data engineering projects from inception to completion.

● Engage in strategic discussions with customers and offer thought leadership to guide their decisions.

● Ensure data quality, integrity, and security throughout the data lifecycle.

Technical Innovation:

● Stay updated with the latest trends and advancements in data engineering and AWS technologies.

● Drive continuous improvement initiatives to enhance data engineering practices and processes.

● Experiment with new tools and technologies to improve data processing efficiency and effectiveness.

What is Required:

● Bachelor's or Master's degree in Engineering or Technology (B.E. / M.E. / B.Tech / M.Tech)

● 15+ years of technical hands-on experience in Data space.

● At least 4 end-to-end implementations of large-scale data projects

● Experience working on projects across multiple geographic regions

● Extensive experience with a variety of projects, including on-premises to AWS migration,modernization, greenfield implementations and cloud-to-cloud migrations.

● Proficiency with AWS data services such as AWS Glue, Redshift, S3, Athena, EMR, Lambda, and RDS.

● Strong understanding of AWS architecture and best practices for data engineering.

● Proficiency in managing AWS IAM roles, policies, and permissions.

● Proficient in SQL and Python for data processing and transformation.

● Strong understanding of data warehousing concepts, ETL/ELT processes, and data modeling.

● Experience with data integration from various sources including batch and real-time data streams.

● Familiarity with data serialization formats such as Avro, Parquet, and ORC.

● Expertise in optimizing data pipelines and query performance.

● Experience with monitoring and troubleshooting data pipelines.

● Proficiency in performance tuning and optimization of distributed computing environments.

● Experience with data governance frameworks and practices.

● Understanding of data lifecycle management and data retention policies.

● Ability to implement and manage data quality frameworks and processes.

● Hands-on experience with big data processing frameworks like Apache Spark, Hadoop, and Kafka.

● Knowledge of stream processing technologies and frameworks.

● Experience with data visualization tools such as PowerBI or Tableau.

What’s in it for you?

The experience of working in a category defining high growth startups in the transformational AI, Decision Science and Big Data Domain.

The opportunity of getting on boarded to the phenomenal growth journey and helping the customers take the next big leap in digital transformation.

The opportunity to work with a diverse, lively and proactive group of techies who are constantly raising the bar on the art of translating mounds of data into tangible business value for clients. Flexible working options available to foster productivity and work/life balance.

Greetings from Colan Infotech!

Role - Data Scientist

Experience - 6+ Years

Job Location - Chennai/Bangalore

Notice Period - Immediate to 30 Days

Primary Skills Needed : AI/ML, Tensorflow, Django, Pytorch, NLP, Image processing,Gen AI,LLM

Secondary Skills Needed : Keras, OpenCV, Azure or AWS

Job Description:-

• Practical knowledge and working experience on Statistics and Operation Research methods.
• Practical knowledge and working experience in tools and frameworks like Flask, PySpark, Pytorch, tensorflow, keras, Databricks, OpenCV, Pillow/PIL, streamlit, d3js, dashplotly, neo4j.
• Good understanding of how to apply predictive and machine learning techniques like regression models, XGBoost, random forest, GBM, Neural Nets, SVM etc.
• Proficient with NLP techniques like RNN, LSTM and Attention based models and effectively handle readily available stanford, IBM, Azure, Open AI NLP models.
• Good understanding of SQL from a perspective of how to write efficient queries for pulling the data from database.
• Hands on experience on any version control tool (github, bitbucket). Experience of deploying ML models into production environment experience (MLOps) in any one of the cloud platforms like Azure and AWS
• Comprehend business issues and propose valuable business solutions.
• Design Factual or AI/profound learning models to address business issues.
• Design Statistical Models/ML/DL models and deploy them for production.
• Formulate what information is accessible from where and how to augment it.
• Develop innovative graphs for data comprehension using d3js, dashplotly and neo4j

Interested candidates send updated resume to

Company Overview

GOVIAFLY CARGO AND LOGISTICS PRIVATE LIMITED is a prominent player in the transportation, logistics, supply chain, and storage industry. Headquartered in Bangalore, we are dedicated to delivering exceptional logistical solutions. With a dynamic team size of 11-50 employees, we specialize in offering comprehensive cargo and logistics services, ensuring efficiency and reliability in each facet of our business. Visit our website at viaflylogistics.com to learn more about our services.

Job Overview

We are seeking a highly motivated Data Science fresher to join GOVIAFLY CARGO AND LOGISTICS PRIVATE LIMITED based in Bangalore Urban. This is a full-time position ideal for candidates with 0 to 1 year of work experience. The successful candidate will play a crucial role in analyzing and interpreting complex data sets to help drive strategic decision-making within the company. Must possess a strong ability in data visualization as an essential skill.

Qualifications and Skills

• Proficiency in data cleaning techniques to ensure data quality and accuracy for reliable insights.
• Strong knowledge of statistical analysis methods to interpret data effectively and draw meaningful conclusions.
• Basic understanding of machine learning principles and algorithms to aid in data-driven decision making.
• Experience with payroll processing, reflecting an understanding of financial data management.
• Data visualization skills to communicate data insights effectively. (Mandatory skill)
• Ability to work independently and collaboratively within a team to achieve common objectives.
• Strong problem-solving skills to address complex data challenges and provide actionable recommendations.
• Excellent communication skills, both written and verbal, to present data findings clearly.

Roles and Responsibilities

• Analyze large datasets to discover trends and patterns that support business objectives.
• Collaborate with team members to understand data requirements and design analytical solutions.
• Develop and implement data models to optimize business processes and improve operational efficiency.
• Create intuitive data visualizations and dashboards to present insights to stakeholders.
• Conduct statistical analysis to evaluate the impact of business strategies and initiatives.
• Support the companys data-driven culture by promoting and educating team members on data importance.
• Assist in the automation of data processing tasks to enhance efficiency and reduce manual intervention.
• Stay updated on industry trends and advancements in data science to apply best practices.