Manager, Data Engineer
Get alerts for roles like this
More Manager, Data Engineer roles in United States — straight to your inbox. No account needed.
Applying to this role? Tailor your résumé to this job description in one click, then download it clean — no watermark, no subscription.
Job Description
With a company culture rooted in collaboration, expertise and innovation, we aim to promote progress and inspire our clients, employees, investors and communities to achieve their greatest potential. Our work is the catalyst that helps others achieve their goals. In short, We Enable Possibility℠.
Job Summary
Strategic Analytics at Arch is a growing team at the forefront of the company’s AI transformation. We design and deploy agentic AI systems and predictive analytics, supported by AI-ready data assets and AI-assisted development practices. These capabilities are becoming increasingly embedded across the enterprise.
Data is central to our mission. We unify internal and external data on modern cloud platforms—including Snowflake and Databricks within the Azure ecosystem—to produce reliable, analytics-ready data assets that support both traditional analytics and emerging AI use cases.
As Manager of Strategic Analytics Services, supporting the Claims Analytics group, you will lead end-to-end delivery of complex data pipelines that put analytics at the center of business processes.
This is a hands-on role that combines execution, technical leadership, and stakeholder partnership, including leading and developing a team of data engineers. You will work closely with business and technical leaders to align priorities, shape scalable data solutions, and deliver measurable outcomes.
You will also guide engineers and reinforce strong delivery practices, while advancing the team’s capabilities in modern data engineering, AI-assisted development, and well-governed, reusable data systems.
Responsibilities
Lead delivery of high-quality data solutions by partnering with stakeholders and coachingdataengineers. Own end-to-end data engineering delivery across the project lifecycle. Build strong partnerships across the organization to align priorities anddeliverdata-related goals. Design clear, analytics-ready data structures byanticipatingdownstream analytical needs. Evaluate and ad