Note: The job is a remote job and is open to candidates in USA. Pinnacle Talent Placement is a mid-to-large healthcare technology company focused on Revenue Cycle Management solutions. They are seeking a Data Engineer to build and maintain production pipelines for their cloud-native data platform, involving migration from legacy systems and ensuring data quality and compliance with HIPAA regulations.

Responsibilities

• Build and maintain ETL/ELT pipelines for healthcare data ingestion and transformation across assigned client environments
• Monitor daily ETL job execution across all active feeds — resolve failures, missing files, and data quality issues independently before they impact revenue collections or payment posting
• Evaluate inbound flat file structure, completeness, and data quality to determine the appropriate ETL configuration and mapping approach
• Design and implement mapping engines and processes for inbound claims (837I/837P), remittance (835), claims status (277), and supplemental payer files — translating file specs into production-ready ingestion logic
• Define and apply mapping rules for new and modified feed configurations
• Implement data quality checks and validation logic to ensure accuracy and completeness of claims, remittance, and status data
• Serve as primary ETL contact for internal teams and external payers — delivering timely status updates to billing ops, revenue cycle leadership, and technical stakeholders
• Write, test, and optimize SQL transformation logic for high-volume healthcare datasets
• Support synchronization of data between operational data stores (ODS), data warehouses, and analytical platforms
• Enforce PHI/HIPAA controls throughout all data processing work
• Assist with migration tasks as the team transitions legacy ETL workflows to Databricks and Azure
• Document pipeline logic, data flows, and known edge cases for team knowledge continuity
• Participate in code review — giving and receiving feedback on implementation quality
• Engage directly with revenue cycle operations, billing teams, or product managers to clarify and document data requirements when specs are incomplete or absent
• Translate business requirements into technical implementation plans for assigned pipeline work — escalating architectural decisions to senior engineers where scope warrants

Skills

• 2–5 years of hands-on experience in data engineering or a closely related technical role
• Bachelor's degree in Computer Science, Information Systems, Data Science, or equivalent practical experience
• Solid understanding of SQL — writes and debugs complex queries and transformations independently
• Hands-on experience with Python for data processing and automation tasks
• Proficiency in at least one ETL/ELT tool — Azure Data Factory, Databricks, SSIS, or equivalent
• Solid understanding of how data moves through ingestion, transformation, and loading stages end-to-end
• Hands-on experience with Azure SQL Database or SQL Server in a production environment
• Demonstrated ability to implement data quality checks and handle exception conditions in pipelines
• Comfortable working in Git-based version control workflows
• Hands-on experience with healthcare transaction formats — 837I/837P, 835, 277 — or ability to learn them quickly in context
• Working knowledge of file delivery processes including SFTP and PGP encryption, and experience monitoring ingestion status
• Working knowledge of healthcare billing form types — UB-04, CMS-1500 — and familiarity with inpatient/outpatient billing and payer adjudication workflows
• Solid understanding of HIPAA requirements and PHI handling expectations in a data engineering context
• Works independently on defined tasks without requiring daily direction
• Comfortable asking the right questions to turn vague business needs into concrete technical requirements — without waiting to be handed a spec
• Communicates blockers and trade-offs clearly to teammates and leads
• Attention to detail in code, data, and documentation
• Collaborative in code review — gives and receives feedback constructively
• Hands-on experience with Databricks, Delta Lake, or Spark
• Hands-on experience with health system source platforms — Epic, MEDITECH, Cerner, or Athena
• Familiarity with Medallion Architecture (Bronze / Silver / Gold pattern)
• Hands-on experience with SSIS, Informatica, or custom middleware integrations
• Comfortable with NoSQL databases such as MongoDB
• Exposure to CI/CD practices for data workflows
• Familiarity with dbt, Great Expectations, or similar data quality frameworks
• Azure Data Engineer Associate (DP-203) certification or working towards it

Company Overview