Position Summary
The Data Engineer will support the design, development, and maintenance of data pipelines and data models that power DataSpring's analytics and data platforms. This role focuses on implementing scalable data solutions, ensuring data quality, and collaborating with senior engineers and stakeholders to deliver reliable data for reporting and analysis. This position provides an opportunity to build hands-on experience with Databricks, Azure SQL, and modern data engineering practices while contributing to enterprise data initiatives and discussions.
The Data Engineer is a full-time, remote, exempt position and reports to the Sr. Director, Data Engineering & Architecture.
Specific Responsibilities
Data Engineering & Architecture
- Build and maintain ETL/ELT pipelines across Databricks, Azure SQL, and downstream gold-layer models supporting priority projects
- Support development and enhancement of enriched data models, including field-level enrichment logic, recency rules, and provider-level enrichment flags.
- Assist in maintaining data logic, including reconciliation between source and target data sources and resolution of duplication and data discrepancies.
- Assist in implementing medallion architecture patterns (bronze → gold), ensuring data quality, traceability, and performance at scale.
Data Quality, Governance & Reliability
- Support identification and resolution of systemic data quality issues, including null handling, soft deletes, authorization flags, and incorrect organizational mappings.
- Support implementation of rules for data in collaboration with product, governance, and engineering stakeholders.
- Assist in documenting (Confluence, mapping workbooks) to serve as a single source of truth for enrichment logic and data behavior.
Cross‑Functional & Vendor Collaboration
- Support collaboration with vendors and partners for vendors providing detailed queries, validation logic, and corrective guidance on upstream data issues.
- Collaborate with product owners and engineering teams to ensure data models align with product defined use cases.
- Support UAT and release readiness by preparing data, validating counts, and resolving last‑mile data defects under tight timelines.
Skills
- Strong foundational SQL skills (complex joins, reconciliation, performance tuning).
- Familiarity with Databricks, Delta Lake, and Azure SQL.
- Basic understanding of data modeling for analytical, operational, and API‑driven use cases.
- Ability to support troubleshooting of messy, evolving enterprise data domains.
- Excellent written and verbal communication, especially for explaining complex data behavior to non‑technical stakeholders.
- Experience using Git, DevOps tools, and CI/CD pipelines for data engineering workflows.
Experience
- 1–3 years of experience in a data engineering or analytics engineering role, including internships or academic projects.
- Demonstrated success contributing to data modernization or migration initiatives in cloud environments.
- Prior experience working with healthcare or other regulated data environments is highly desirable.
- Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or a related field.
- Azure Data Engineer Associate or related certification (preferred).
- Coursework or certification in AI/ML (preferred but not required).
Who We Are
DataSpring is the trusted data connector at the core of healthcare. For more than 25 years, we have powered the industry with the largest and most complete healthcare data foundation in the U.S., including more than 4.8 million provider data records sourced directly from providers and member data representing 75% of covered lives supplied by health plans. By improving how essential information flows across the system, DataSpring helps healthcare operate more efficiently, accurately, and with greater confidence.
What You Get
At DataSpring, you will do meaningful work at the intersection of healthcare, data, and technology, helping solve complex problems that make the healthcare system work better. You will collaborate with experienced professionals who care deeply about accuracy, trust, and meaningful impact in a fully remote environment.
DataSpring offers competitive compensation and a comprehensive benefits package for full-time employees, including medical, dental, and vision coverage, a 401(k) with company contributions and matching, paid parental leave, tuition assistance, and generous paid time off. We are committed to investing in our people and supporting professional growth over time.
Equal Opportunity Employer
DataSpring is proud to be an equal opportunity employer and is committed to fostering a workplace where all individuals are valued, respected, and empowered.
Employment decisions at DataSpring are made without regard to race, color, religion, sex, national origin or ancestry, age, marital status, disability, protected veteran status, personal appearance, sexual orientation, gender identity or expression, familial status, family responsibilities, matriculation, political affiliation, genetic information, source of income, place of residence, or any other characteristic protected by law. DataSpring does not tolerate unlawful discrimination or harassment of any kind.
Applicants have rights under the Family and Medical Leave Act (FMLA), Equal Employment Opportunity (EEO), and the Employee Polygraph Protection Act (EPPA). If you need a reasonable accommodation to apply for a posted position, please contact the DataSpring People & Culture team at [email protected] or 202-517-0436.
