Job Summary:

We are looking for an experienced Databrick Lead with strong hands-on experience in AWS, Databricks, Oracle, PySpark, ADF, DATA Quality, and PL/SQL. The candidate will be responsible for designing scalable data solutions, optimizing data pipelines, and providing technical leadership to the data engineering team.

Key Responsibilities:

- Design and develop scalable data pipelines using AWS, Databricks, ADF, and Oracle.

- Develop data processing and transformation solutions using PySpark and Spark SQL.

- Develop and optimize complex SQL and PL/SQL queries.

- Implement Databricks Lakehouse, Delta Lake, Unity Catalog, and Lakehouse Federation.

- Manage Databricks Views, permissions, privileges, and access controls.

- Implement Databricks Asset Bundles (DABs), Jobs, Workflows, and Triggers.

- Integrate Oracle data with AWS and Databricks platforms.

- Work with AWS services such as S3, Glue, Lambda, IAM, and CloudWatch.

- Perform data quality, validation, reconciliation, and performance optimization.

- Provide technical guidance, code reviews, and mentorship to the data engineering team.

Tech Stack:

- AWS, Databricks, Oracle, PySpark, PL/SQL, Unity Catalog, Lakehouse Federation, Databricks Asset Bundles, Views & Access Management.

Candidate Profile:

- 8+ years of experience in Data Engineering/Data Platforms.

- Strong hands-on experience in AWS, Databricks, Oracle, PySpark, ADF, PL/SQL, and Data quality.

- Experience with advanced Databricks capabilities and real-world implementation.

- Strong technical leadership, problem-solving, and communication skills.