Data Engineer

Overview Weare looking for a hands-on Data Engineer to design, build, and optimizescalable data pipelines on the Databricks Lakehouse platform.

involvescollaborating with analysts, data scientists, and business teams to deliverreliable, analytics-ready data assets. Key

Responsibilities Build and maintain batch and streaming data pipelines using PySpark and Databricks . Implement medallion architecture (Bronze, Silver, and Gold layers). Optimize Spark jobs for performance and cost efficiency.

Ensure data quality, lineage, and governance using Unity Catalog and automated validation. Integrate data from APIs, databases, files, and event streams. Implement CI/CD, version control, and workflow orchestration.

Monitor, troubleshoot, and document data pipelines and data models. Collaborate with stakeholders to translate business requirements into technical solutions. Required

Qualifications 3–5 years of hands-on data engineering experience. Strong PySpark skills, including DataFrames, Spark SQL, UDFs, and performance tuning . Proven experience building production pipelines on Databricks.

Working knowledge of Delta Lake, including ACID transactions, time travel, merge/upsert, and schema evolution . Advanced SQL and strong Python programming skills . Experience with Azure, AWS, or GCP cloud platforms .

Understanding of data modelling, Lakehouse architecture, and ETL/ELT patterns. Familiarity with Git and CI/CD practices. Preferred

Qualifications Databricks Data Engineer Assoc