Manager, Data Engineer (Remote)

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 coaching data engineers. Own end‑to‑end data engineering delivery across the project lifecycle. Build strong partnerships across the organization to align priorities and deliver data‑related goals. Design clear, analytics‑ready data structures by anticipating downstream analytical needs. Evaluate and adopt new technologies and data sources to improve capability and efficiency. Automate data ingestion and integration to reliably connect internal and external data sources. Document data sources, definitions, and technical solutions to support transparency and reuse. Reinforce strong delivery hygiene (version control, code review, automated testing, CI/CD, and operational readiness/monitoring). Apply agentic, AI‑assisted coding practices to accelerate delivery while maintaining appropriate controls. Build agent‑ready data assets, including semantic layer components (ontology, taxonomy, domain models) and governed access. Provide retrieval‑ready context (RAG pipelines, vector stores, knowledge bases) when needed. Desired Skills Data Engineering Strong programming expertise in Python and SQL, including data engineering frameworks, large‑scale data manipulation, and governed AI‑assisted development practices Apache Spark proficiency (PySpark preferred) and experience with distributed data processing, including building scalable pipelines and optimizing performance for large‑scale datasets Cloud data platform proficiency (Snowflake, Databricks, Azure ecosystem fundamentals) Data warehousing and modeling fundamentals (schema design, conformed definitions, performance optimization) Data quality and observability practices (testing, reconciliation, monitoring) Analytics & AI Readiness Insurance data modeling for analytics and actuarial‑ready data structures MLOps familiarity supporting operationalized analytics and models Semantic modeling skills (business definitions, metrics, ontology/taxonomy/domain models) Business definition standardization for reuse across BI and AI use cases Leadership & Operating Model Self‑directed execution and ownership in a distributed environment, combined with strong cross‑functional collaboration, stakeholder partnership, and team building Strong problem‑solving and critical thinking skills, including the ability to decompose complex challenges Clear communication across technical and business audiences, with the ability to adapt effectively in ambiguous and evolving environments Required Skills 6+ years’ experience of hands‑on development in Python and distributed processing environments (e.g., Spark) 2–3+ years of technical leadership or project delivery ownership experience Hands‑on Databricks experience highly preferred Education College degree in Computer Science, Engineering, Statistics, Mathematics, Actuarial Science, Data Analytics, or equivalent. Compensation and Benefits For individuals assigned or hired to work in the location(s) indicated below, the base salary range is provided. Range is as of the time of posting. Position is incentive eligible. $100,500 - $174,000/year Total individual compensation (base salary, short & long‑term incentives) offered will take into account a number of factors including but not limited to geographic location, scope & responsibilities of the role, qualifications, talent availability & specialization as well as business needs. The above pay range may be modified in the future. Arch is committed to helping employees succeed through our comprehensive benefits package that includes multiple medical plans plus dental, vision and prescription drug coverage; a competitive 401k with generous matching; PTO beginning at 20 days per year; up to 12 paid company holidays per year plus 2 paid days of Volunteer Time Offer; basic Life and AD&D Insurance as well as Short and Long‑Term Disability; Paid Parental Leave of up to 10 weeks; Student Loan Assistance and Tuition Reimbursement, Backup Child and Elder Care; and more. Learn more on available benefits. #J-18808-Ljbffr Arch Capital Group Ltd.