Senior ETL​/Data Integration Engineer

Job Description

We are seeking a ETL / Data Integration Engineer to support a healthcare data initiative focused on building a unified “golden provider record.” This role will be responsible for aggregating, transforming, and enriching provider data from multiple systems to drive better referral decision‑making and provider insights.

• Design, develop, and optimize SQL‑based data pipelines across Postgre
  
  SQL and Snowflake environments
• Integrate data from multiple sources including claims, payer feeds, and credentialing systems
• Build and maintain golden provider records through data aggregation, normalization, and enrichment
• Perform data profiling, quality validation, reconciliation, and cleansing to ensure accuracy and reliability
• Implement entity matching, deduplication, and survivorship logic to support a single source of truth
• Collaborate with cross‑functional teams to ensure data supports downstream applications and analytics

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances.

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• 5+ years of hands‑on experience in data engineering, ETL, or data integration roles, with a strong focus on building and managing data pipelines
• Advanced SQL expertise across Postgre
  
  SQL and Snowflake, including complex query development, optimization, and large‑scale data processing
• Proven experience designing and implementing ETL/data integration workflows, including extracting, transforming, and loading data from multiple heterogeneous data sources
• Strong hands‑on experience with data transformation, enrichment, and profiling, ensuring consistency, usability, and business alignment of datasets
• Demonstrated expertise in data quality management, including data validation, reconciliation, cleansing, and ongoing monitoring processes
• Experience with data modeling for master data / golden record solutions, including schema design to support unified, high‑quality datasets
• Hands‑on experience with entity resolution techniques, including matching, deduplication, and survivorship logic to create a single source of truth
• Ability to work with complex datasets across multiple domains, integrating data from systems such as claims, payer feeds, or credentialing platforms; experience working with healthcare datasets (claims, provider, payer, credentialing data)
• Exposure to secure data handling and access management practices