Data Engineer

Data Engineer

Full Time

Columbus, OH

And Health is a healthcare technology company created to radically improve access and outcomes for the most challenging chronic health conditions. We are driven by the goal of making world‑class specialty care accessible and affordable to all. We partner with health systems, community health centers, and independent practices to remove barriers to care to ensure all people have access to the care they deserve.

We are building the modern data platform that powers And Health’s analytics, reporting, operational workflows, product integrations, and AI initiatives. This is a senior, hands‑on infrastructure and pipeline engineering role. You will own the systems that ingest, transport, transform, and serve data – the foundational layer that everything else at And Health depends on.

Healthcare data is messy. Partner feeds arrive in inconsistent formats with no warning when schemas change. Source systems span decades of technical debt: flat files, HL7 feeds, proprietary exports, and undocumented APIs. Compliance requirements are strict and non‑negotiable. We need someone who has been through this before and knows how to build ingestion and transformation systems that absorb that complexity, so that by the time data reaches the warehouse, it is clean, consistent, and trustworthy.

We expect engineers to leverage AI tools thoughtfully to move faster, and to bring good judgment about where automation helps and where it introduces risk.

• Build and own the ingestion layer. Design scalable frameworks for onboarding new healthcare partner data sources: file‑based, API‑based, streaming, with standardized validation, error handling, and schema evolution support.
• Design and maintain production‑grade data pipelines that are idempotent, incremental where appropriate, and built to recover gracefully from failures.
• Build the data quality and observability infrastructure. Implement schema validation, row‑count reconciliation, freshness checks, anomaly detection, and alerting at the platform level.
• Own orchestration, scheduling, and pipeline reliability. Every pipeline has clear SLAs, dependency management, failure alerting, and documented recovery procedures. You build the runbooks, the backfill tooling, and the incident response patterns.
• Manage the warehouse infrastructure layer. Performance tuning, partitioning and clustering strategies, cost optimization, access control, and environment management in Big Query.
• Translate complex healthcare source systems into clean, standardized raw and staging datasets that analytics engineers and analysts can build on with confidence. This includes messy, semi‑structured partner data from EHRs, claims systems, pharmacy platforms, and billing feeds.
• Build reusable ingestion and transformation frameworks that the team can extend without reinventing the wheel. Think config‑driven pipelines, shared libraries, and standardized patterns.
• Manage integrations with healthcare partners and external data sources, including HRSA, CMS, Medicaid, FDA Orange Book, and federal drug pricing reference datasets. Own the ingestion contracts, handle schema drift, and ensure no data is silently lost or corrupted.
• Ensure HIPAA‑compliant security, privacy, and access controls throughout the data lifecycle, including PII detection and masking, role‑based access, encryption, and audit logging.
• Define and enforce data contracts between source systems and the data platform, and between the platform and downstream consumers. When something changes upstream, you know about it before it causes damage.

• Bachelor’s degree in Computer Science, Information Systems, Engineering, Mathematics, or a related technical field preferred.

• 5+ years of hands‑on data engineering experience, with a track record of building and operating production data systems.
• Built ingestion systems from scratch. Dealt with unreliable source systems, inconsistent file formats, undocumented APIs, and schema changes that arrive without warning. Built frameworks that handle these problems systematically.
• Strong infrastructure and platform thinking.…