Job Design, build, and optimize ETL/ELT pipelines for batch and streaming data.
- Develop and maintain data warehouses and data lakes (e.g., Snowflake, BigQuery, Redshift).
- Collaborate with data scientists, analysts, and product teams to understand data needs.
- Ensure data quality, reliability, and observability across pipelines.
- Build and manage orchestration workflows (e.g., Airflow, Prefect, Dagster).
- Implement best practices for data modeling, partitioning, and performance tuning.
- Monitor and troubleshoot data infrastructure issues in 5+ years of experience in data engineering or a related role.
- Proficiency in SQL and Python (or Scala/Java).
- Experience with cloud platforms (AWS, GCP, or Azure).
- Hands-on with big data tools: Spark, Kafka, dbt, or similar.
- Familiarity with data warehousing concepts and dimensional modeling.
- Strong understanding of CI/CD and version control (Git).
Nice to Have:
- Experience with real-time/streaming pipelines (Kafka, Flink, Kinesis).
- Exposure to ML pipelines or MLOps tooling.
- Knowledge of data governance and data catalog tools (e.g., Atlan, Alation).
Data Engineer - Python/ETL • Bangalore