Data Engineering Manager

📋 Description

• • Build and lead an exceptional Data Engineering team. Hire great engineers, coach and develop the team, grow senior technical leaders, set a high performance bar, and create a culture of ownership and continuous improvement.
• • Use AI to increase both speed and quality. Develop and implement a point of view on how AI can improve the full analytics engineering lifecycle, from stakeholder engagement, team management, to design and development.
• • Set the technical direction for Data Engineering. Bring strong opinions grounded in experience while encouraging first-principles thinking. Guide architectural decisions and ensure the team builds systems that are simple, scalable, reliable, and appropriate for the problems we're solving.
• • Partner across the company. Work closely with Infrastructure, Analytics, Data Science, Product, Engineering, Finance, and other teams to understand how the business works, define clear ownership, and build a data ecosystem that enables teams to move faster and make better decisions.
• • Shape the future of the Data organization. Partner with the Head of Data on organizational design, hiring, roadmap prioritization, and the investments needed to support Imprint's continued growth.
• • Our Data Engineering priorities include:
• • Make Imprint's data legible. Lead the evolution of our enterprise data warehouse into a clear, consistent, and trusted representation of how Imprint's business works. Ensure important business concepts have well-designed models, clear definitions, and intuitive relationships that make our data easier to understand and use.
• • Raise the bar for analytics engineering. Establish strong principles and patterns for data modeling, transformation, testing, documentation, and ownership across our dbt and Snowflake environment. Create the technical standards that allow our data models to remain coherent as the business grows more complex.
• • Scale analytics engineering beyond the Data Engineering team. Create a development model where domain experts can turn their knowledge into high-quality, reusable data models without Data Engineering sitting in the critical path. Define the right boundaries, abstractions, review processes, and ownership model to make distributed contribution successful.
• • Build the platform that makes this possible. Partner closely with Infrastructure to create the tooling, workflows, and guardrails that make contributing to our enterprise data warehouse fast and safe. Make the right way the easiest way.
• • WHAT WE LOOK FOR
• • Experience introducing AI-assisted workflows at scale.
• • Experience in a high-growth startup, fintech, or another environment where data correctness and reliability are critical.
• • A track record of building and leading high-performing data or analytics engineering teams, including hiring exceptional talent, developing engineers, managing performance, and growing senior technical leaders.
• • Deep expertise in analytics engineering with dbt, with experience turning complex business domains into data models that are understandable, reusable, and trusted.
• • Strong technical judgment. You can evaluate data models and architecture, identify unnecessary complexity, challenge your team's thinking, and provide direction without needing to personally implement every solution.
• • Strong SQL fluency and enough familiarity with Python and modern software engineering practices to engage deeply with the team's technical work.
• • The ability to move comfortably between strategy and detail, pairing strong opinions with intellectual curiosity and first-principles thinking.
• • PERKS & BENEFITS
• • Competitive compensation and equity packages
• • Leading configured work computers of your choice
• • Flexible paid time off
• • Fully covered, high-quality healthcare, including fully covered dependent coverage
• • Additional health coverage includes access to One Medical and the option to enroll in an FSA
• • 20 weeks of paid parental leave for the primary caregiver and 8 weeks for all new parents
• • Access to industry-leading technology across all of our business units, stemming from our philosophy that we should invest in resources for our team that foster innovation, optimization, and productivity