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Develop and maintain scalable data pipelines using Databricks, Python, and PySpark while automating ETL workflows with Delta Live Tables. Optimize Spark performance and ensure data quality and governance across all engineering solutions.
This is a remote position.
3–6 years of experience in Data Engineering.
Strong knowledge of SQL, Python, and PySpark.
Hands-on experience with Databricks and Apache Spark.
Understanding of Spark optimization, partitioning, and shuffling.
Experience with Delta Lake, Z-Ordering, and VACUUM.
Experience building ETL pipelines using Delta Live Tables (DLT).
Knowledge of Apache Airflow or Azure Data Factory.
Understanding of data governance and data quality.
Develop and maintain scalable data pipelines using Databricks, Python, and PySpark.
Build and automate ETL workflows using Delta Live Tables (DLT).
Optimize Spark jobs through partitioning, shuffling, and performance tuning.
Implement Delta Lake optimization techniques, including Z-Ordering and VACUUM.
Manage data orchestration using Airflow or Azure Data Factory.
Ensure data quality, governance, and pipeline performance.
Collaborate with cross-functional teams to deliver efficient data engineering solutions.
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