Description

You will design and build cloud-native data pipelines and lakehouse architectures using Azure, Snowflake, and Databricks.

This role is on-site.

Responsibilities

• Develop and maintain data transformation workflows using dbt, PySpark, and SQL.
• Implement CI/CD pipelines with GitHub Actions and manage code via Git.
• Architect data lakes using ADLS Gen2, Parquet, and lakehouse formats like Iceberg or Delta Lake.
• Deploy and manage infrastructure on Azure Cloud, with AWS or GCP experience as a plus.
• Collaborate on data modeling and orchestration using tools like Airflow or Fabric Data Factory.

Required Skills

• 5+ years of hands-on Data Engineering experience.
• Strong proficiency in SQL and Python (PySpark preferred).
• Experience with Azure Cloud, Snowflake, Microsoft Fabric, or Databricks.
• Practical knowledge of lakehouse concepts (Iceberg/Delta Lake) and object storage (ADLS Gen2).
• Proficiency with dbt (Core or Cloud) for data transformation.
• Experience with GitHub for version control and Pull Request-based development.
• Understanding of CI/CD pipeline implementation.

Preferred Skills

• Experience with orchestration tools such as Airflow or Dagster.
• Background in Healthcare/Payer domain (Claims, Provider, Clinical).

Key Skills

Education

Any Graduate