Technical Data Engineer -Databricks
ShyftLabs (company site, opens in a new tab)4+ yrsCoimbatoreHybridDirect career pageEst. 9–16 LPA
Posted 2d ago
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Job description
Structured overview of role & requirements
About This Role
- Design, develop, and maintain scalable ETL/ELT pipelines on the Databricks Lakehouse Platform using PySpark, SQL, and Python.
- Integrate and manage data from multiple sources including databases, Amazon S3, files, and REST APIs, while implementing business logic, data transformations, and dimensional data models.
- Optimize Spark workloads and Databricks Jobs/Workflows, ensure data quality with validations and monitoring, and manage Delta Lake tables using Medallion Architecture.
Minimum Requirements
- Strong expertise in Python, PySpark, and advanced SQL.
- Hands-on experience with Databricks Lakehouse Platform including Unity Catalog, Delta Lake, Databricks Jobs, and Medallion Architecture.
- Experience integrating data through REST APIs and managing large volumes of structured and semi-structured data.
- Work Experience Required: Minimum 4 years in Data Engineering with at least 2 years hands-on Databricks experience.
Ideal Candidate Profile
- Experienced in building and optimizing production-ready data engineering solutions on Databricks, with strong focus on end-to-end pipeline ownership.
- Skilled in data modeling (Star/Snowflake schemas, SCDs) and data warehousing best practices matched with practical knowledge of Delta Lake and Spark performance tuning.
- Comfortable working with cross-functional teams, CI/CD pipelines, and integration tools; experience in data governance is a plus but not mandatory.