Data Engineer

SUMMARY

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
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, 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)