Sr. Data Engineer(Azure Databricks & scala spark)

Job Description & Summary:

1. hands-on experience in PySpark development on Azure Databricks.

2. end-to-end ownership of data pipeline development, from coding and version control to build, deployment, and production validation in a modern lakehouse environment.

3. PySpark and Scala codebases, build Spark JARs using Maven, and execute/validate them on Azure Databricks using Spark Submit and Databricks Workflows.

Skill: Apache Spark on Azure Databricks, Azure Databricks, Pyspark, SQL, Scala and Hadoop

Responsibilities:

1. Design, develop, and maintain scalable batch data pipelines using Apache Spark on Azure Databricks.

2. Build Spark executable JARs using Maven and manage
   dependencies.

3. Execute and validate Spark jobs using Spark Submit on Azure Databricks with custom runtime arguments and I/O paths.

4. Implement and manage Delta Lake components (Delta Tables, Delta Live Tables).

5. Work with Hive Metastore and Unity Catalog for metadata, governance, and access control.

6. Making code changes in Scala/PySpark projects and taking them through to production execution.

....... 6+ years of overall experience in Data Engineering, with strong focus on: Apache Spark (core APIs, transformations/actions,
RDD/DataFrame/Dataset APIs).

Good To Have skill sets:

Proficiency in Pyspark and Scala for Spark development
(primary language for repositories).,Strong SQL skills for complex queries, transformations, and performance tuning.., Solid understanding of advanced Data Engineering concepts (e.g., data modeling in lakehouse, incremental/batch patterns, CDC, SCDs, data quality frameworks).