Technical Data Engineer (Databricks)

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Skills you'll use

What you'll do

• Design, develop, and maintain scalable ETL/ELT pipelines using Databricks,
• PySpark, and SQL.
• ● Integrate data from multiple sources, including databases, Amazon S3, files, and REST APIs.
• ● Build data pipelines with Databricks Unity Catalog.
• ● Implement business logic, data transformations, and dimensional data models.
• ● Create, schedule, monitor, and optimize Databricks Jobs and Workflows.
• ● Design and manage Delta Lake tables using Medallion Architecture (Bronze, Silver,Gold).
• ● Ensure data quality through validations, error handling, logging, and monitoring.
• ● Optimize Spark workloads for performance, scalability, and reliability.
• ● Collaborate with cross-functional teams to deliver production-ready data solutions.

Who can apply

• Strong expertise in Python, PySpark, and Advanced SQL.
• ● Hands-on experience with the Databricks Lakehouse Platform.
• ● Good understanding of Unity Catalog, Delta Lake, Databricks Workflows/Jobs,
• Clusters, Notebooks, Repos, and Medallion Architecture.
• ● Experience integrating with REST APIs for data ingestion and data export.
• ● Strong knowledge of ETL/ELT development, batch processing, incremental loading,
• and data transformation.
• ● Experience with data modeling (Star Schema, Snowflake Schema, Fact & Dimension
• tables, SCD concepts).
• ● Understanding of data warehousing concepts and best practices.

About ShyftLabs

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