Data Engineer — Healthcare / CMS Data / Snowflake / Python

Job Summary We are seeking a dynamic and detail-oriented Data Engineer specializing in Healthcare data, CMS (Centers for Medicare & Medicaid Services) datasets, and cloud-based data solutions. In this role, you will leverage your expertise in Snowflake, Python, and a broad array of big data technologies to design, develop, and optimize scalable data pipelines and architectures. Your work will enable advanced analytics, reporting, and insights for healthcare organizations, ensuring data integrity, security, and accessibility. This position offers an exciting opportunity to contribute to impactful healthcare data initiatives within a fast-paced, innovative environment.

Duties

• Design and develop robust ETL (Extract, Transform, Load) pipelines using Python and Talend to facilitate seamless data integration from diverse sources such as AWS cloud services, Oracle databases, and SQL Server environments.
• Build and maintain scalable data warehouses utilizing Snowflake, and other cloud databases to support complex healthcare analytics.
• Collaborate with cross-functional teams to model healthcare data using dimensional modeling techniques for efficient query performance and reporting.
• Implement data management best practices including data model design, query optimization, and metadata management to ensure high-quality data assets.
• Write, troubleshoot, and optimize SQL queries, stored procedures, and data transformations.
• Support data modeling, source-to-target mapping, schema design, and data integration documentation.
• Perform data validation, reconciliation, data quality checks, and defect analysis.
• Troubleshoot pipeline defects, data issues, job failures, and production data problems.
• Support version control practices, code documentation, technical documentation, and team delivery standards.
• Collaborate with data analysts, business stakeholders, developers, QA, and technical leads as needed.
• Support Agile delivery activities, including sprin...