Job Opportunities API

Machinify is a leading healthcare intelligence company with expertise across the payment continuum, delivering unmatched value, transparency, and efficiency to health plan clients across the country. Deployed by over 85 health plans, including many of the top 20, and representing more than 270 million lives, Machinify brings together a fully configurable and content-rich, AI-powered platform along with best-in-class expertise. We’re constantly reimagining what’s possible in our industry, creating disruptively simple, powerfully clear ways to maximize financial outcomes and drive down healthcare costs. As a Staff Data Engineer on the Migrations team , you are the end-to-end technical and operational owner of client migrations. You will drive the full lifecycle, from deep-dive legacy analysis to production deployment, while orchestrating collaboration across Operations, Client Success, Product, Data Science and Platform Engineering. You don't just implement; you own the outcome. This is a high-trust, high-autonomy role for someone who can think like an architect, execute like a senior engineer, and coordinate like a program manager — all on the same project. You'll own the problem space from discovery to go-live, making the defining architectural decisions and writing the code that brings them to life.   What You’ll Do Lead discovery & technical due diligence — get to the bottom of poorly documented legacy systems (ETL, stored procedures, reporting layers, file feeds), reconstruct the business logic, and capture it in the lineage maps, mapping specs, and risk analyses everyone builds from. Reverse-engineer complex legacy systems using agents— you will be responsible for reverse-engineering complex, undocumented legacy systems (SSIS packages, stored procedures) where business logic is embedded, not documented. You must be able to reconstruct the intent of these systems to build modern, stable equivalents. Drive ambiguity to resolution — spot the unknowns early, own the open questions, and pull answers from clients, SMEs, and Operations instead of waiting to be unblocked. Architect & build the migration pipelines — turn intricate legacy logic into production-grade Airflow DAGs and Spark jobs on the Machinify platform, edge cases, payer-specific carve-outs, and business-rule exceptions included, owning the full flow from ingestion through reconciliation to steady-state handoff. Make and document the hard architectural calls — own the decisions that matter (pipeline design, partitioning strategy, validation approach) and leave a clear trail of the reasoning so others can learn from and build on it. Prove correctness at scale — build automated reconciliation frameworks that confirm, with confidence, that migrated output matches the source down to the row. Own the program end to end — be the single technical owner from kickoff through go-live and hypercare: scope, sequence, and track the work, surface risks before they bite, align Operations, Client Success, Platform Engineering, SMEs, and the client, and drive UAT through to sign-off. Raise the bar for the practice — Institutionalize migration knowledge by codifying runbooks and retrospectives, mentor L3/L4 engineers to build independent capability, and turn recurring migration pain points into scalable, reusable tooling. What You Bring 8+ years a s a hands-on Data Engineer or Software Engineer, with demonstrated experience independently owning complex, multi-stakeholder technical projects from start to finish . Strong Python and SQL — fluent with complex, unfamiliar legacy code, not just greenfield work. Apache Spark — deep understanding of distributed processing, performance tuning, partitioning, and debugging at scale. Apache Airflow — advanced; comfortable designing and authoring production DAG architectures from scratch. AI-assisted development — actively uses