Python Data Engineer

We are seeking a highly skilled Python Data Engineer with deep experience in CMS datasets (MOR, MMR, MAO) and a strong understanding of healthcare regulations and compliance standards (HIPAA). This role is ideal for a data-driven professional who thrives in cloud-native environments and is passionate about building robust, scalable, and efficient pipelines that drive healthcare innovation.

Key Responsibilities :

Design, develop, and maintain scalable ETL pipelines for CMS datasets using GCP Dataflow (Apache Beam) and Python

Architect and manage BigQuery data warehouses, ensuring optimal performance and cost-efficiency

Implement and manage Airflow DAGs for workflow orchestration and scheduling

Ensure end-to-end data quality, lineage, validation, and governance in alignment with HIPAA and CMS standards

Optimize large-scale healthcare datasets using partitioning, clustering, sharding, and efficient query patterns in BigQuery

Collaborate within Agile teams using tools like Jira and Confluence for sprint planning and documentation

Monitor, troubleshoot, and improve pipeline reliability and performance across the full data lifecycle

Qualifications :

Bachelor's degree in Computer Science, Information Systems, or related field

3+ years of experience in cloud-based data engineering, preferably with healthcare datasets

Strong proficiency in Python, GCP Dataflow, and Apache Beam

Expert-level knowledge in BigQuery, including schema design, performance tuning, and advanced SQL

Hands-on experience with Airflow forthe  orchestration of complex data workflows

In-depth understanding of data warehouse design, including star / snowflake schemas, normalization, and denormalization

Strong analytical skills for query and data optimization

Familiarity with Agile methodologies and collaboration tools (Jira, Confluence)

Knowledge of CMS datasets (MOR, MMR, MAO) and healthcare data privacy / compliance standards (HIPAA)