Role & responsibilities

We are looking for experienced Data Engineers with robust hands-on experience in PySpark and Snowflake, along with DataOps/Production Support experience and exposure to AI/GenAI technologies.

The candidate will be responsible for developing and supporting scalable data pipelines, monitoring production data workflows, troubleshooting data issues, and leveraging AI capabilities to improve data engineering and operational processes.

Key Responsibilities

Design, develop, and maintain scalable data pipelines using PySpark, Python, and SQL.

Work extensively with Snowflake for data ingestion, transformation, validation, and optimization.

Monitor and support data pipelines and ETL/ELT jobs in production.

Troubleshoot job failures, data quality issues, performance problems, and production incidents.

Perform Root Cause Analysis (RCA) and implement permanent fixes.

Ensure data availability,



accuracy, and quality across data platforms.

Handle incident, problem, and change management activities within defined SLAs.

Optimize PySpark jobs and Snowflake queries for performance and cost efficiency.

Automate repetitive DataOps and support activities.

Leverage AI/GenAI tools and techniques to improve data engineering, monitoring, troubleshooting, and automation.

Collaborate with Data Scientists, Data Engineers, Business Analysts, and other technology teams.

Maintain technical documentation, operational procedures, and support runbooks.

Preferred candidate profile

The ideal candidate should have a robust combination of Data Engineering + DataOps/Production Support + AI/GenAI exposure.

📌 Urgent Hiring For Data Engineer Role Chennai
🏢 Orcapod Consulting Services
📍 Chennai