Data Engineering Manager
Leads the Data Engineering organization, building a high-performing team and setting technical direction for analytics engineering, data modeling, and the enterprise warehouse. The role requires deep dbt expertise, strong SQL and Python fluency, and experience scaling reliable data development through platforms and standards.
About the job
Responsibilities
- Build and lead an exceptional Data Engineering team, including hiring, coaching, developing senior technical leaders, setting a high performance bar, and fostering ownership and continuous improvement.
- Develop and implement a perspective on using AI to improve the analytics engineering lifecycle, including stakeholder engagement, team management, design, and development.
- Set the technical direction for Data Engineering and guide architectural decisions for simple, scalable, reliable systems.
- Partner with Infrastructure, Analytics, Data Science, Product, Engineering, Finance, and other teams to define ownership and build a data ecosystem that enables faster, better decisions.
- Partner with the Head of Data on organizational design, hiring, roadmap prioritization, and investments supporting company growth.
- Evolve the enterprise data warehouse into a clear, consistent, and trusted representation of the business.
- Establish principles and patterns for data modeling, transformation, testing, documentation, and ownership across the dbt and Snowflake environment.
- Create a development model that enables domain experts to contribute high-quality, reusable data models safely and independently.
- Define boundaries, abstractions, review processes, and ownership models for distributed data development.
- Partner with Infrastructure to build tooling, workflows, and guardrails that make enterprise data warehouse contributions fast and safe.
Requirements
- Experience introducing AI-assisted workflows at scale.
- Experience in a high-growth startup, fintech, or another environment where data correctness and reliability are critical.
- Track record of building and leading high-performing data or analytics engineering teams, including hiring, performance management, engineer development, and growing senior technical leaders.
- Deep expertise in analytics engineering with dbt and experience modeling complex business domains into understandable, reusable, trusted data models.
- Strong technical judgment in data modeling and architecture.
- Strong SQL fluency and familiarity with Python and modern software engineering practices.
- Ability to move between strategy and technical detail while applying first-principles thinking.
Compensation & Benefits
- Competitive compensation and equity packages.
- Flexible paid time off.
- Fully covered healthcare, including dependent coverage.
- Access to One Medical and an optional FSA.
- 20 weeks of paid parental leave for the primary caregiver and 8 weeks for all new parents.
- Work computer of choice and access to industry-leading technology.
Skills
AI, Analytics Engineering, dbt, Snowflake, SQL, Python, Data Modeling, Data Warehousing, Data Architecture, Data Transformation, Data Testing, Data Documentation, Modern Software Engineering
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