Design and build scalable data pipelines in Databricks using Spark (PySpark/Scala) .
Develop batch and streaming data workflows from diverse data sources into cloud data lakes (Delta Lake).
Optimize Spark jobs for performance, scalability, and reliability.
Work with stakeholders to understand data requirements and deliver clean, transformed datasets.
Implement and manage data governance and security with Unity Catalog or other catalog tools.
Collaborate with DevOps teams to deploy notebooks and jobs via CI/CD pipelines.
Develop documentation and reusable components to standardize data engineering practices.
Monitor and troubleshoot data pipeline performance and errors.
3+ years of hands-on experience with Databricks and Apache Spark .
Strong programming skills in Python or Scala .
Deep understanding of Delta Lake , Medallion Architecture , and ELT/ETL processing.
Experience working with cloud services such as Azure Data Lake , AWS S3 , or GCP Cloud Storage .
Solid SQL skills for querying structured and semi-structured data.
Knowledge of Databricks Workflows , Jobs API , and Cluster management .
Familiarity with data orchestration tools like Azure Data Factory , Airflow , or DBT .
Experience with CI/CD tools such as GitHub Actions, Azure DevOps, or Jenkins.
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