Data Engineer

DataSpring

$100K — $115K *
US-AnywhereRemote in United States
Healthcare
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 1-3 years in data engineering or analytics engineering, including internships or academic projects
  • Experience with data modernization or migration in cloud environments
  • Strong SQL skills, including complex joins and performance tuning
  • Familiarity with Databricks, Delta Lake, and Azure SQL
  • Excellent communication skills for explaining data behavior to non-technical stakeholders
  • Azure Data Engineer Associate certification preferred

Responsibilities

  • Build and maintain ETL/ELT pipelines across Databricks and Azure SQL
  • Enhance data models with field-level enrichment logic and recency rules
  • Maintain data logic through reconciliation between source and target
  • Implement medallion architecture ensuring data quality and performance
  • Identify and resolve systemic data quality issues
  • Document enrichment logic and data behavior as a source of truth
  • Collaborate with vendors and partners to address upstream data issues

Benefits

  • Medical, dental, and vision coverage
  • 401(k) with company contributions and matching
  • Paid parental leave
  • Tuition assistance
  • Generous paid time off
  • Strong support for professional growth in a remote environment
Full Job Description
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).


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.

The pay range for this role is:

100,000 - 115,000 USD per year (Remote (United States))

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