Data Engineer

Responsibilities:

• 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 production

Key Requirements:

• 5+ years of experience in data engineering or a related role
• Proficiency in SQL and Python (or Scala/Java)
• Experience with cloud platforms (AWS)
• 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)