Manager, Data Engineer (Remote)

Arch Capital Group Ltd. is a company focused on collaboration, expertise, and innovation, aiming to enable progress for its clients and communities. The Manager of Strategic Analytics Services will lead the delivery of complex data pipelines, ensuring analytics are central to business processes while guiding a team of data engineers and collaborating with stakeholders to shape scalable data solutions.

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

Requirements:

• 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
• College degree in Computer Science, Engineering, Statistics, Mathematics, Actuarial Science, Data Analytics, or equivalent
• 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)
• 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
• 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