SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Abacus Insights is transforming healthcare data management for health plans. The company has raised $100M and is building a platform that breaks down data silos to create a single, trusted data foundation for better clinical and financial decision-making.
As Manager of Client Data Engineering, you will lead a globally distributed team of 10–12 data engineering professionals within the TechOps/Technical Implementation organization. This is a hands-on leadership role that combines technical depth with people management and operational discipline.
Key responsibilities include:
- Leading end-to-end client implementations for healthcare data use cases, ensuring timely delivery aligned with client expectations
- Providing technical leadership across ETL, data mapping, and clinical data integration workflows
- Managing distributed and offshore teams to coordinate delivery, align priorities, and maintain operational rigor
- Mentoring engineers and new hires while building a collaborative, performance-driven culture
- Optimizing interoperability workflows and CMS Interoperability implementation processes
- Supporting delivery management, resource planning, and prioritization with cross-functional teams
- Defining team success metrics, monitoring progress, and driving continuous improvement
- Promoting adoption of tools and technologies that improve scalability, quality, and efficiency
You bring 7+ years of data engineering experience, including client-facing implementations. You have demonstrated technical leadership and hands-on expertise in ETL, data integration, and complex data transformations. You are proficient in Python, PySpark, and advanced SQL, with experience in AWS-based architectures, Databricks, and Snowflake. You have practical experience with version control (GitHub/GitLab) and a data-driven approach to problem-solving. Experience with GenAI and agentic development is valued. Healthcare data knowledge (clinical/claims data, payer systems, healthcare analytics) is preferred but not required. A Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or related field is expected.
