Job Description:
The Director, Analytics Engineering and AI leads the data engineering group and owns the curated, certified data foundation the business relies on to make decisions. The leader is accountable for a cohesive, coordinated data model covering both product and enterprise data. They also build the certified semantic layer that makes this foundation reliably and safely accessible to AI. They lead a team of senior and principal engineers through a significant platform transition towards AI while sustaining the revenue-, pipeline-, and finance-critical reporting the company depends on every day. This is a hands-on, player-coach role: the right leader sets direction and grows the team, but also rolls up their sleeves - modeling data, writing and reviewing SQL and dbt code leveraging AI, and getting into the weeds to solve the hardest problems alongside their engineers.
Who you're committed to being:
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You move fluidly between technical detail and executive-level storytelling, adjusting your message to fit the room.
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You build trust and alignment among Revenue, Marketing, and Finance by earning agreement, not demanding it.
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You balance vision with execution.
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Training and elevating other analytics practitioners is part of how you define your own success.
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You treat your solutions and leadership style as always improving, not finished.
What you'll do:
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Lead, develop, and grow the Analytics Engineering team - setting technical direction, standards, and priorities - while sustaining business-critical reporting (revenue, product, marketing, finance) without interruption.
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Own a single, unified data transformation and model spanning both product/behavioral and enterprise (GTM, finance) data.
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Establish and expand the certified contextual layer that ensures reliable and safe access to the data warehouse for analytics. This layer builds on a governed data dictionary and metrics store. It also covers lineage, freshness, ownership, access, entity relationships, and business knowledge.
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Drive the migration of transformation logic out of integration/middleware tooling into governed, certified models owned by the team.
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Partner across Data Analytics, Data Engineering, Data Architecture, Data Governance to plan and execute cross-team initiatives.
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Serve as a senior partner to collaborators across Revenue, Marketing, Finance, GTM, and Success. Translate business needs into scalable, balanced analytics solutions. Communicate mentorship, compromises, and outcomes to senior leadership.
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Set and uphold engineering standards - modeling conventions, certification practices, code quality, and documentation.
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Stay hands-on in the work: build and review data models, write and debug SQL and dbt code leveraging AI, dig into data-quality issues, and take direct ownership of the most complex or highest-stakes problems.
Experience you'll bring:
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Familiarity with high-performance OLAP serving layers (e.g., ClickHouse) for product- or customer-facing analytics.
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Experience reducing reliance on integration/middleware tooling by migrating transformation logic into governed models.
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Experience partnering with a data governance function on company-wide standards, schema/version control, and PII classification.
Requirements:
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Requires a minimum of 12 years of related or equivalent experience; or 8+ years and an advanced degree.
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Demonstrated hands-on expertise in data curation, transformation, and dimensional/medallion data modeling on a modern cloud data stack (e.g., Snowflake, dbt).
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Proven breadth of data modeling across both product/behavioral event data and enterprise GTM/financ
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Current, hands-on technical depth in making productive use of AI. This is a player-coach role, not a purely managerial one.
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Experience leading a team... For full info follow applicatio link.