Senior Data Engineer

Requirements

• 3–7 years of hands-on experience building production-grade data pipelines
• Strong expertise in SQL, including query optimization and complex transformations
• Strong Python programming skills for data engineering workloads
• Experience with Spark/PySpark or equivalent distributed processing frameworks
• Strong understanding of data modeling, ETL/ELT, CDC, incremental processing, and partitioning
• Experience with workflow orchestration tools such as Dagster, Airflow, or Prefect
• Experience working with AWS or Azure cloud platforms
• Strong focus on data quality, observability, validation, and monitoring
• Experience building scalable datasets for analytics and machine learning use cases
• Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field

Responsibilities

• Design, build, and maintain scalable batch ETL/ELT and CDC pipelines
• Own data ingestion from client systems into the data platform
• Build reliable, idempotent, incremental, and backfill-safe data pipelines
• Model and transform raw data into trusted analytical and ML-ready datasets
• Develop and optimize Spark/PySpark and SQL workloads for large-scale processing
• Implement data quality checks, lineage, monitoring, and alerting mechanisms
• Support machine learning feature pipelines and analytics platforms
• Optimize storage formats, partitioning strategies, and query performance
• Collaborate with ML, product, and engineering teams to deliver reliable data solutions
• Drive best practices for scalability, reliability, and maintainability across the data stack

Job Details Gurugram - Hybrid (2–3 days on-site)

Interview Process

• Technical Round (Python & SQL)
• System Design Round
• Culture Fit Round