$ cat jobs/director-client-data-engineering-abacus-insights-979a792cd6d8.json
Director, Client Data Engineering
About Us Abacus Insights is transforming how data works for health plans. Our mission is simple: make healthcare data usable, so the people responsible for care and cost decisions can act faster, with confidence. We help health plans break down data silos to create a single, trusted data foundation. That foundation powers better decisions—so plans can improve outcomes, reduce waste, and deliver better experiences for members and providers alike. Backed by $100M from top investors, we’re tackling big challenges in an industry that’s ready for change. Our platform enables GenAI use cases by delivering clean, connected, and reliable healthcare data to support automation, prioritization, and decision workflows—and it’s why we are leading the way. Our innovation begins with people. We are bold, curious, and collaborative—because the best ideas come from working together. We embrace the thoughtful use of AI and automation to drive innovation and efficiency, and we look for individuals who are curious and adaptable—those excited to leverage emerging technologies to enhance how we work—while keeping human insight, connection, and our clients at the center of every decision. Ready to make an impact? Join us and let’s build the future together. About the Role The Director, Client Data Engineering is a pivotal leader within our TechOps / Technical Implementation organization, responsible for leading a globally distributed team of approximately ______ data engineering professionals. This role sits at the intersection of client delivery, technical execution, and people leadership, with a primary focus on driving successful client implementations and scaling high‑quality data engineering practices. This is a hands‑on leadership role that combines technical depth with operational excellence. The director will guide feature delivery teams, partner closely with cross‑functional stakeholders, and ensure reliable execution across complex healthcare data use cases, including ETL workfl
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