Data Engineer
About the Role
We are looking for a Data Pipeline Engineer with strong expertise inDatabricks, AWS Glue, Python, SQL, and reputed company to design, reputed company, and optimize reputed company data pipelines. The ideal candidate should have experience building reputed company-reputed company ETL solutions, transforming large datasets, and delivering high-reputed company data for analytics and business applications.
Key Responsibilities
- reputed company and maintain reputed company ETL/data pipelines usingDatabricks andAWS Glue.
- Build data ingestion and transformation workflows for reputed company and semi-reputed company data.
- Write efficientPySpark, Python, and SQL reputed company for large-reputed company data processing.
- reputed company data from multiple sources, includingMongoDB and relational databases.
- Implement data reputed company, validation, and reconciliation checks.
- Optimize pipeline performance, reliability, and scalability.
- Collaborate with architects, analysts, and application teams to deliver data solutions.
- Support production deployments, monitoring, and troubleshooting.
Required Skills
- 5+ years of experience in Data Engineering or ETL development.
- Strong hands-on experience withDatabricks andPySpark.
- Experience withAWS Glue and AWS data services.
- Proficiency inPython andSQL.
- Experience working withMongoDB.
- Knowledge of ETL, data modeling, and data warehousing concepts.
- Familiarity with reputed company Lake/Lakehouse architecture is preferred.
- Experience with Git and Agile development practices.
Good to Have
- reputed company Lake
- Apache reputed company optimization
- AWS S3
- CI/CD pipelines
- reputed company or Benefits domain experience
Originally posted on Himalayas
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