Manager, Data Engineering and Analytics

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Role

The Manager, Data Engineering and Analytics leads and actively contributes to the delivery of enterprise data analytics. This is a hands-on role that is responsible for managing Data Engineers, Data Analysts and a Product Owner while owning the design, development, and upkeep of data management solutions and reporting methodology. Drives innovative initiatives to transform data interpretation and utilization, setting standards for data-driven decision-making and empowers the team with actionable insights.

This role is hybrid, in-office three days per week and the rest can be remote.

Essential Responsibilities

  • Manages and coaches Data Engineers, Data Analysts, and a Product Owner, providing technical direction, prioritization, and performance feedback.
  • Partners with the Product Owner to define, prioritize, and maintain the data and analytics backlog.
  • Leads delivery using Scrum / Agile practices, including sprint planning, refinement, reviews, and retrospectives.
  • Balances feature delivery, platform health, and technical debt.
  • Remains hands-on with architecture, development, complex data pipelines, modeling decisions, and priority engineering work.
  • Owns and supports a cloud-based data environment such as Microsoft Fabric or AWS, including environment setup, deployment pipelines, monitoring, and operational support.
  • Establishes standards for data pipelines, semantic models, testing, and release management.
  • Oversees production operations, incident response, and root cause analysis.
  • Identifies opportunities to apply analytics and AI to improve efficiency, insight quality, and decision making.
  • Owns data governance practices, including data quality checks, documentation, lineage, and metric definitions.
  • Enforces role based access, environment segregation (Dev/UAT/Prod), and secure data access patterns.
  • Ensures consistency and trust across reports, dashboards, and semantic models.
  • Other duties as assigned.

Qualifications

  • 10+ years of experience in data engineering, analytics engineering, or BI delivery in production environments.
  • High school diploma or GED required.
  • Bachelor’s degree preferred.
  • Demonstrated experience leading teams or acting as a technical lead with ownership of delivery outcomes.
  • Strong SQL skills with experience designing scalable ELT/ETL pipelines and data models (warehouse/lake house).
  • Hands on experience supporting cloud based data platforms, including monitoring and operational support.
  • Experience working in Scrum / Agile delivery models and collaborating closely with a Product Owner.
  • Experience with lake houses, warehouses, pipelines, semantic models, deployment pipelines.
  • Azure/AWS cloud experience (identity, security, storage, automation).
  • Python experience.
  • Experience supporting analytics or data platforms used by AI or machine learning solutions.

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