Data Engineer

DataSpring is a trusted data connector in the healthcare industry, with over 25 years of experience. They are seeking a Data Engineer to support the design, development, and maintenance of data pipelines and models, ensuring data quality and collaborating with various stakeholders.

Responsibilities:

• 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
• 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
• 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

Requirements:

• 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
• 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
• 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
• 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
• 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
• Coursework or certification in AI/ML