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-protected 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

📌 Senior Data Engineer (Gurugram)
🏢 ClanX
📍 Gurugram