Design and develop scalable ETL/ELT pipelines using Apache Spark on Databricks.

• Build and maintain robust data lakes and data warehouses (Delta Lake, Lakehouse architecture).

• Optimize data flows for performance, scalability, and cost-efficiency on the Databricks platform.

• Collaborate with data analysts, scientists, and other engineers to integrate data from diverse sources.

• Implement data quality checks, monitoring, and alerting solutions.

• Develop CI/CD pipelines for data jobs and workflows.

• Support the migration of legacy data systems to the Databricks ecosystem.

• Contribute to data governance and security best practices

Solid proficiency in Apache Spark, PySpark, SQL,Python and Delta Lake.

Experience with cloud platforms (Azure, AWS, or GCP), preferably Azure Databricks, Azure Data Factory, and Azure Synapse.

Deep understanding of data modeling, data warehousing, and ETL processes.

Hands-on experience with job orchestration tools like Databricks Workflows, Airflow, or similar.

📌 Senior Data Brick Engineer (Ahmedabad)
🏢 Zenithive Engineering
📍 Ahmedabad