Job Description:

We are seeking a highly skilled and proactive Databricks Platform Support Engineer to join our onsite data engineering team. In this role, you will be responsible for maintaining, supporting, and optimizing large-scale data pipelines on the Databricks platform, while ensuring the stability, performance, and scalability of mission-critical data operations. The ideal candidate will have deep hands-on experience with Apache Spark, Azure Data Factory, Snowflake, and ETL tools, as well as a strong understanding of cloud data ecosystems. This role involves close collaboration with data engineers, BI analysts, and operations teams to ensure timely and reliable data delivery across business units.

Key responsibilities:

• Monitor, support, and troubleshoot Databricks jobs, data pipelines, and platform-level issues

• Design, develop, and optimize ETL workflows using Databricks, Azure Data Factory, and Informatica

• Manage data ingestion and transformation from various sources, including Teradata, S3, APIs, and structured data feeds

• Ensure high performance, scalability, data quality, and secure access across the platform

• Implement and maintain scheduling, orchestration, and monitoring workflows (e.g., Airflow, Autosys, CTRL-M)

• Collaborate with BI and data engineering teams to support reporting and analytics delivery

• Maintain and version control code using Git and adhere to SDLC best practices.

Professional Skills:

• Databricks: Python, Spark, Delta Lake.

• Azure Cloud Services: Azure Data Factory, Azure Synapse, Azure Blob Storage

• Snowflake: Snowpipe, zero-copy cloning, RBAC (role-based access control),ETL Tools: Informatica, SSIS, Alteryx.

• Strong coding proficiency: SQL, PL/SQL, PySpark.

• Workflow orchestration: Airflow, Autosys, or CTRL-M, Version control: Git

• 10+ years of overall experience in data engineering and platform support

• 3+ years of hands-on experience with Databricks in a production environment

• Exposure to BI tools such as Power BI or Tableau

• Background in supporting production-grade data platforms, with a focus on incident response and performance tuning.

• Experience working in a high-availability, enterprise cloud environment.