Manager, Data Engineering & Analytics

We are looking for a Manager, Data Engineering & Analytics to own the architecture, delivery, and evolution of our enterprise data platform. This is a hybrid leadership and hands‑on role: you’ll manage a team of data engineers while staying close to the data modeling, pipeline architecture, and business automation work that keeps the platform running. You will act as the bridge between business stakeholders and technical execution — scoping requirements, architecting scalable solutions in Google Big Query and dbt, orchestrating integrations through Snap Logic, and overseeing our Tableau environment.

Manage and mentor a team of data engineers, providing regular feedback, technical coaching, performance reviews, and career development support. Own the team’s Jira board and lead Agile/Scrum ceremonies, including backlog grooming, sprint planning, task estimation, and delivery tracking. Build a culture of technical excellence, accountability, clear documentation, and continuous learning.

Architect and maintain our data transformation layer in dbt, ensuring modular, tested, and well‑documented data models. Manage and optimize our enterprise data warehouse in Google Big Query, including performance tuning, cost management, and access controls. Build and monitor ELT pipelines and automated workflows using Snap Logic and REST APIs to connect core SaaS platforms and enterprise systems. Design and run proof‑of‑concepts to evaluate emerging technologies and architectural enhancements.

Administer Tableau, including server/site governance, user permissions, licensing, performance monitoring, and content promotion. Establish and champion best practices for data modeling, version control (Git), CI/CD, and technical documentation. Ensure data integrity, reliability, and security compliance across all ingestion and reporting layers.

Partner directly with cross‑functional business leaders to translate strategy into technical data roadmaps and actionable user stories. Coordinate UAT and validate data deliverables alongside business partners. Maintain SOPs and data dictionaries to drive data literacy across the organization.

• 5+ years in Data Engineering, Analytics Engineering, or Enterprise Data Solutions.
• 2+ years of formal people management, or demonstrated experience leading engineering squads, sprint planning, and managing backlogs in Jira.
• Production‑level experience designing, optimizing, and managing a cloud data warehouse (Google Big Query or Snowflake preferred).
• Advanced dbt experience — architecting and deploying projects using macros, tests, incremental models, and documentation.
• Hands‑on experience building integrations using an enterprise iPaaS (e.g., Snap Logic, Workato, Fivetran, Boomi) and third‑party REST APIs.
• Hands‑on experience administering a modern BI platform (Tableau user management, data sources, and site administration preferred).
• Proven ability to communicate technical trade‑offs to non‑technical business partners and document complex, end‑to‑end data workflows.
• Preferred:
  Experience with Python or another scripting language for data pipelines and automation.
• Certifications such as dbt Certified Developer, GCP Professional Data Engineer, or Tableau Certified Administrator.
• Background in data governance and security compliance frameworks (SOC 2, GDPR) and data quality monitoring.
• Experience integrating AI/LLM tools into data workflows — e.g., connecting platforms via Model Context Protocol (MCP), or building with Claude/Gemini APIs for automation, documentation, or analytics use…