Top Data Engineer Jobs in Pune

As a Business Technology Solutions Associate Consultant, you will manage project lifecycles, translate business needs into solutions, mentor team members, and drive technology project deliverables in big data and cloud environments.

Design, build, and optimize data pipelines and ETL processes in Azure Databricks, ensuring performance, reliability, and scalability while collaborating with teams to translate business needs into technical solutions.

As a Data Engineer III, you will collaborate with stakeholders to design and develop data management solutions, analyze data, and enhance data quality using advanced analytics and engineering techniques.

Lead the design and optimization of data infrastructures, mentor engineers, and develop scalable data solutions while ensuring data integrity and security.

The Azure Data Engineer will maintain data infrastructure, develop data pipelines, analyze data, and enhance data quality while collaborating with teams.

As a Data Engineer, you will implement data pipelines and analytics to support decision-making using AWS technologies and Machine Learning.

Lead design and optimization of data pipelines and architectures, mentor engineers, collaborate with teams, and drive technical strategies in data engineering.

The Data Engineer role involves developing and deploying AI/ML solutions, building data engineering solutions, and applying statistical methods for insights.

As a Data Engineer, you will create and maintain data pipelines, support data scientists, and design data solutions on cloud platforms.

The Data Engineer will develop data pipelines, process large datasets, ensure data quality, and support AI and ML applications.

Assist in building scalable data workflows, support AI/ML projects, and contribute to mentor-led development and research on GCP features.

Design, implement, and maintain data pipelines using Elasticsearch and data warehousing solutions, integrate data sources, and ensure data accuracy while collaborating with cross-functional teams.

The Snowflake Data Engineer will develop and manage large-scale data pipelines, collaborate with stakeholders, and optimize data engineering solutions using Snowflake.

The Data Engineer will design and maintain data pipelines and infrastructure, collaborate with teams, and ensure data accuracy for client solutions.

Lead the design and development of scalable data engineering products, optimize data processes, and mentor junior team members in a healthcare analytics context.

The Senior Data Engineer will design and implement data ingestion processes, develop scalable data pipelines, and collaborate with teams to integrate data sources.

The Data Engineer will build and maintain data pipelines, ensuring quality and performance while supporting business analytics and operations.

The Data Automation Test Engineer will validate data migration and ETL processes while developing a QA framework, automation scripts, and collaborating with cross-functional teams.

The Senior Data Engineer develops and supports data streams, ensures data quality, collaborates on data requirements, and leads a team in data engineering tasks.

The Data Engineer will produce quality data models, gather data requirements, ensure data quality, and support integration efforts in the healthcare domain.

The Sr. Big Data Engineer will design, develop, and maintain scalable data extraction frameworks and ETL/ELT pipelines, optimizing data processing systems while collaborating with cross-functional teams.

Design and maintain scalable data pipelines for complex datasets, enhance data processing systems, and collaborate across teams to ensure data quality and performance optimization.

The role involves developing and maintaining scalable data pipelines, ensuring data quality, collaborating with teams, and optimizing data performance.

The role involves designing, developing, and maintaining large scale data engineering solutions while collaborating with stakeholders on data governance and analytics.

The role involves designing and developing data solutions using Databricks, focusing on data pipeline architecture, optimization, and reporting.