Senior Databricks Engineer

We are looking for a Senior Databricks Engineer with 7+ years of experience in data engineering and strong hands-on expertise in Databricks and Apache Spark. The ideal candidate will design and build scalable data pipelines, optimize large-scale data processing, and work with cloud-based data platforms.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines using Databricks and Apache Spark.
• Develop and optimize PySpark/Spark jobs for large-scale data processing.
• Build reliable ETL/ELT pipelines using Databricks workflows, Delta Lake, and SQL.
• Implement data transformations, data quality checks, and performance optimization.
• Work with cloud data platforms such as AWS, Azure, or GCP.
• Optimize Spark jobs, cluster configurations, partitioning, joins, and data processing performance.
• Collaborate with data engineers, data scientists, analysts, and business teams to deliver data solutions.
• Implement best practices for CI/CD, version control, monitoring, and production support.
• Troubleshoot data pipeline and performance issues in production environments.

Required Skills

• 7+ years of experience in Data Engineering.
• Strong hands-on experience with Databricks.
• Strong expertise in Apache Spark / PySpark.
• Experience with Delta Lake, Databricks Workflows, and Spark SQL.
• Strong proficiency in Python and SQL.
• Experience building and optimizing large-scale ETL/ELT pipelines.
• Experience with at least one cloud platform: AWS, Azure, or GCP.
• Good understanding of data warehousing, data modeling, and distributed data processing.
• Experience with Git and CI/CD practices.

Preferred Skills

• Experience with Unity Catalog and Databricks governance.
• Experience with Azure Data Factory, AWS Glue, or similar orchestration tools.
• Knowledge of streaming technologies such as Kafka or Spark Structured Streaming.
• Experience with Infrastructure as Code or cloud automation.
• Databricks certifications are a plus.