Manager, Data Engineer

Salary: $100,500 - 174,000 per year Requirements:

• We need 6+ years of hands-on development experience in Python and distributed processing environments such as Spark.
• We require 2-3+ years of technical leadership or project delivery ownership experience.
• We strongly prefer practical experience with Databricks.
• We look for a college degree in Computer Science, Engineering, Statistics, Mathematics, Actuarial Science, Data Analytics, or an equivalent field.
• We value strong programming ability in Python and SQL, including data engineering frameworks, large-scale data manipulation, and governed AI-assisted development practices.
• We seek proficiency with Apache Spark, preferably PySpark, and experience building scalable pipelines and optimizing performance for large datasets.
• We look for cloud data platform experience across Snowflake, Databricks, and the Azure ecosystem.
• We value fundamentals in data warehousing and modeling, including schema design, conformed definitions, and performance tuning.
• We need familiarity with data quality and observability practices such as testing, reconciliation, and monitoring.
• We prefer experience with insurance data modeling for analytics and actuarial-ready structures.
• We value MLOps awareness for operationalized analytics and models.
• We look for semantic modeling capability, including business definitions, metrics, ontology, taxonomy, and domain models.
• We expect self-directed ownership in a distributed environment, along with strong cross-functional collaboration, stakeholder partnership, and team building.
• We value strong problem-solving and critical thinking skills with the ability to break down complex challenges.
• We need clear communication skills across technical and business audiences, especially in ambiguous and changing environments.

• We lead delivery of high-quality data solutions by partnering with stakeholders and coaching data engineers.
• We own end-to-end data engineering delivery across the full project lifecycle.
• We build strong partnerships across the organization to align priorities and deliver data-focused goals.
• We design clear, analytics-ready data structures by anticipating downstream analytical needs.
• We evaluate and adopt new technologies and data sources to improve capability and efficiency.
• We automate data ingestion and integration to connect internal and external sources reliably.
• We document data sources, definitions, and technical solutions to promote transparency and reuse.
• We reinforce strong delivery practices, including version control, code review, automated testing, CI/CD, and operational readiness and monitoring.
• We apply agentic, AI-assisted coding practices to accelerate delivery while maintaining proper controls.
• We build agent-ready data assets, including semantic layer components and governed access.
• We provide retrieval-ready context such as RAG pipelines, vector stores, and knowledge bases when needed.
• We lead and develop a team of data engineers while working closely with business and technical leaders to shape scalable data solutions and measurable outcomes.

• Agentic AI
• AI
• Azure
• CI/CD
• Cloud
• Databricks
• MLOps
• Python
• PySpark
• RAG
• SQL
• Snowflake
• Spark
• Embedded
• Support

More:

We are Arch, a company with a culture grounded in collaboration, expertise, and innovation, focused on enabling progress for our clients, employees, investors, and communities. Our Strategic Analytics team is growing and sits at the forefront of our AI transformation, designing and deploying agentic AI systems and predictive analytics supported by AI-ready data assets and AI-assisted development practices. We work on modern cloud platforms, including Snowflake and Databricks within the Azure ecosystem, to create reliable, analytics-ready data assets for traditional analytics and emerging AI use cases. This hands-on Manager of Strategic Analytics Services role supports our Claims Analytics group and combines technical leadership, execution, and stakeholder partnership. We offer a competitive compensation package with incentive eligibility and comprehensive benefits, including medical, dental, vision, prescription drug coverage, a 401k with matching, PTO starting at 20 days, paid holidays, volunteer time off, life and disability insurance, paid parental leave, student loan assistance, tuition reimbursement, backup care, and more.

last updated 33 week of 2026