Job Description:
Key Responsibilities
- Design, develop, and maintain scalable data pipelines using Databricks and PySpark
- Build robust ETL/ELT workflows for batch and near real‑time data processing
- Write optimized and efficient SQL queries for data transformation, validation, and analysis
- Work with large-scale distributed datasets using Spark-based processing frameworks
- Perform data ingestion from multiple sources (APIs, files, databases) into data lake/lakehouse architecture
- Ensure data quality, integrity, and consistency through validations and monitoring
- Optimize pipeline performance and cost (partitioning, caching, query tuning, etc.)
- Collaborate with cross-functional teams (Data Ops, Business, Analytics) to deliver data solutions
- Troubleshoot pipeline failures and implement proactive monitoring and alerting
- Maintain proper documentation for data models, transformations, and workflows
Required Skills & Experience
- Robust hands-on experience in:
- Databricks (Lakehouse platform, notebooks, jobs, clusters)
- PySpark / Apache Spark




- Advanced SQL (joins, window functions, performance tuning)
- Solid understanding of ETL concepts, data warehousing, and data modeling
- Experience building scalable data pipelines for structured and semi-structured data
- Familiarity with data lake / delta lake architecture
- Good understanding of performance optimization techniques in Spark and SQL
- Experience with version control (Git) and deployment practices
- Strong problem-solving and analytical skills
Good to Have
- Experience with cloud platforms (AWS preferably)
- Exposure to CI/CD pipelines (Jenkins)
- Knowledge of Delta Lake, Unity Catalog, or similar governance tools
- Understanding of data quality frameworks / monitoring tools
- Experience working in Agile / Scrum teams
Location:

This position can be based in any of the following locations:

Chennai

Current Guardian Colleagues: Please apply through the internal Jobs Hub in Workday

📌 Senior Engineer (Chennai)
🏢 India
📍 Chennai