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Job Description & How to Apply Below
We are seeking a talented Azure Data Engineer with strong expertise in Azure Databricks, specifically in PySpark and SQL, to join our data team. You will play a key role in building secure, scalable data pipelines and implementing robust data governance strategies.
Key Responsibilities:
Design and implement ETL/ELT pipelines using Databricks and PySpark.
Develop high-performance SQL queries and optimize Spark jobs.
Collaborate with data scientists, analysts, and business stakeholders to understand data needs.
Ensure data quality and compliance across all stages of the data lifecycle.
Implement best practices for data security and lineage within the Databricks ecosystem.
Participate in CI/CD, version control, and testing practices for data pipelines.
Required Skills:
Proven experience with Databricks (data permissions, lineage, audits).
Strong hands-on skills with PySpark and Spark SQL.
Solid experience writing and optimizing complex SQL queries.
Familiarity with Delta Lake, data lakehouse architecture, and data partitioning.
Experience with cloud platforms like Azure or AWS.
Understanding of data governance, RBAC, and data security standards.
Preferred Qualifications:
Databricks Certified Data Engineer Associate or Professional.
Experience with tools like Airflow, Git, Azure Data Factory
Exposure to streaming data and real-time processing.
Knowledge of Dev Ops practices for data engineering.
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