Top Data Engineer Jobs in Pune

As a Data Engineer, you will build and maintain data lakes, optimize data pipelines, and collaborate with business stakeholders to enhance data processing efficiency.

The Data Engineer III will collaborate with business stakeholders to develop data management solutions, conduct data analysis, design analytic algorithms, and optimize performance of data systems. This role requires advanced technical and behavioral skills, emphasizing healthcare data analytics.

The Data Engineer will manage data infrastructure projects, optimize data pipelines, and create analytics tools, requiring expertise in Python and SQL.

As a Data Engineer, design and develop diverse data solutions, create data pipelines, ensure data quality, and implement ETL processes in collaboration with cross-functional teams.

As a Data Engineer, collaborate to design data models and develop data pipeline solutions. Involve in improving data delivery and providing analytical insights using ELT processes.

Lead the design and automation of analytic data engineering products; optimize data processes and provide insights using statistical methodologies and machine learning while mentoring team members.

The Data Engineer will design and implement ETL pipelines, migrate data, and ensure data modeling for various projects, especially within HR.

The Data Engineer will develop distributed data engineering solutions on the cloud, manage data pipelines, and ingest high-volume stream data. Key technologies include AWS, SQL, and Python.

Lead the design of enterprise-scale data pipelines, optimize architectures, ensure performance, and mentor engineers. Collaborate with cross-functional teams to align infrastructure with business needs.

The Business Analyst II will develop workflows, manage data quality, and support reporting projects using Alteryx and SQL, while collaborating with cross-functional teams.

As a Data Engineer, you'll implement complex features, maintain analytics models, mentor juniors, and drive improvements with a focus on customer-centric development.

The Data Engineer will design scalable data solutions using Snowflake, develop SQL procedures, build ETL/ELT pipelines, and optimize cloud data architecture.

The Data Engineer is responsible for building ETL pipelines, working with SQL, GCP, Python/Airflow, and managing data conversion. Experience in HR project migration is required.

The Data Engineer will implement data pipelines and analytics solutions using AWS technologies, collaborate with stakeholders, and optimize data processes.

As a Senior Data Engineer at Atlassian, you will build and maintain data pipelines, manage a data lake, and optimize data ingestion processes while collaborating with business stakeholders.

The role involves designing, developing, and maintaining data models and ETL pipelines using Python, SQL, and DBT, ensuring efficient data management for analysis-ready datasets.

The Data Engineer will lead the design and deployment of AI-driven data solutions, focusing on Vantage AI. Key tasks include model building and data orchestration.

The Senior Data Engineer will develop data products, manage data models, and build ELT pipelines while ensuring data quality and integrity.

The Senior Data Engineer will design, build, and maintain data warehouse solutions, ensuring data integrity and optimizing data processes.

As a Data Engineer, you will design, implement, and test analytic solutions, develop client relationships, and manage data engineering lifecycle.

The Data Engineer will build infrastructure tools to support trading teams, optimize data processes, and coordinate with global teams, ensuring efficient data delivery and coding standards.

The Senior Data Engineer will design, implement, and optimize data solutions, particularly using Power BI, and collaborate with cross-functional teams to meet business requirements.

Interns will assist in building data workflows, transforming data, developing ML models, and participating in team discussions under guidance.

As a Data Engineer, you will transform data into valuable insights, develop data pipelines, and support data scientists while ensuring data quality.

The role involves designing and maintaining data integration infrastructure, building data pipelines, and supporting advanced analytics projects using AWS and Snowflake.