Posted on: 04/06/2026
Role Overview :
We are seeking a skilled and detail-oriented Data Engineer with strong expertise in PySpark and Databricks to design, build, and optimize scalable data pipelines. The ideal candidate will have hands-on experience in data warehousing, ETL processes, and modern data lake architectures, with the ability to translate business requirements into robust technical solutions.
Key Responsibilities :
- Design, develop, and optimize large-scale data pipelines using PySpark and Databricks
- Build and maintain ETL workflows for data extraction, transformation, and loading across multiple sources
- Develop scalable data solutions for Data Warehousing and Data Lake environments
- Translate business requirements into technical specifications and low-level ETL design documents
- Ensure data quality, integrity, and performance optimization across pipelines
- Collaborate with cross-functional teams including analysts, architects, and business stakeholders
- Troubleshoot and resolve data-related issues in production environments
Required Skills & Experience :
- Strong experience in Data Warehousing, ETL, Data Integration, and Data Lake projects
- Hands-on expertise in Databricks for developing and deploying ETL solutions
- Proficiency in PySpark for large-scale data processing
- Strong understanding of data management ecosystems and architecture
- Experience with at least one database system: Redshift, Snowflake, SQL Server, Oracle, Teradata, or Azure
SQL
- Solid SQL skills and experience in performance tuning
- Ability to independently design and deliver complex data solutions
Good to Have :
- Experience in Pharma / Life Sciences domain
- Exposure to cloud platforms (AWS/Azure)
Educational Qualification :
- B.E./B.Tech / MCA / BCA / Computer Science or related field
- Minimum 60% throughout academics
Did you find something suspicious?
Posted by
Posted in
Data Engineering
Functional Area
Data Engineering
Job Code
1641829