We are looking for a Senior Data Engineer with 5+ years of experience to design, build, and optimize scalable ELT/ETL pipelines across our modern data stack. You will own ingestion, data modeling, orchestration, and performance tuning across Snowflake and cloud storage.

Key Responsibilities

- Build robust batch and streaming ingestion pipelines using PySpark or Python.
- Design modular, tested dimensional models (star/snowflake schemas) in Snowflake using dbt.
- Develop, schedule, and maintain enterprise Apache Airflow DAGs and automated alerts.
- Optimize Snowflake performance, query execution, clustering, and compute costs.
- Implement automated data quality checks, CI/CD deployment pipelines, and Git best practices.

Requirements

- Experience: 5+ years of hands-on data engineering in production environments.
- Core Skills: Expert SQL, advanced Python, and distributed processing with PySpark.
- Contemporary Data Stack: Strong production experience with Snowflake, dbt (incremental models, macros), and Airflow.
- Cloud & DevOps: Hands-on experience with AWS, GCP, or Azure, plus Docker, Git, and CI/CD pipelines.
- Architecture: Solid understanding of data modeling, performance profiling, and cost governance.

📌 Data Engineer (Hyderabad)
🏢 RandomTrees
📍 Hyderabad