Analytics Engineering Manager

About the Company

EvolutionIQ’s mission is to deliver state-of-the-art technology that helps insurance claims teams make claims handling more accurate, fair, and efficient. We have been named one of Inc.’s Best Workplaces and Built In’s Best Places to work.

Responsibilities

• Lead the design, development, and maintenance of centralized data warehouse layers using dimensional modeling
• Own and optimize the modern data stack (MDS) for performance and reliability
• Set standards for software engineering practices including Git, CI/CD, and data testing
• Partner with Data Science and Business Analytics to translate business logic into reusable data models
• Manage, mentor, and support a high-performing team of analytics engineers
• Conduct regular 1-on-1s and define clear performance goals and career growth paths
• Manage team sprint planning, prioritization, and roadmap

Requirements

• 5+ years in analytics engineering, data engineering, or technical data analytics
• 1-2+ years of experience directly managing or leading engineers
• Expert-level SQL skills
• Deep understanding of data warehousing, ETL/ELT, and modeling methodologies (Kimball, Data Vault)
• Hands-on experience with Snowflake, BigQuery, or Databricks
• Proficiency with dbt (data build tool)
• Proficiency in Python or similar for data scripts and orchestration
• Familiarity with Git workflows and CI/CD pipelines
• Exceptional communication skills for bridging technical and business stakeholders

Preferred Qualifications

• Experience with data orchestration tools like Airflow, Prefect, or Dagster
• Familiarity with data governance, security, and access control frameworks
• Background in high-growth startups or scaling tech environments