Lead Analytics Engineer in United

It is probably not the right fit if you want a fully established stack, narrowly defined tickets, clean source data, or frequent day-to-day direction. We are looking for a senior builder who is comfortable with ambiguity, can bring order to fragmented operational data, and enjoys owning a foundational platform.

• 6+ years in analytics engineering, data engineering, BI engineering, or a similar role, with experience building or materially modernizing a warehouse, analytics platform, BI strategy, or governed reporting environment. \n

• Strong SQL and hands-on experience building production data models, plus practical experience with ELT/ETL, ingestion, orchestration, testing, observability, documentation, and data lineage. \n

• Experience with a modern cloud warehouse-Snowflake strongly -and a transformation framework such as dbt, SQLMesh, or a comparable production-grade workflow. \n

• Python or similar scripting experience for automation, ingestion, validation, or API integrations. \n

• Strong experience with semantic modeling and a modern BI or semantic-layer tool. Omni, Looker, LookML, Cube, AtScale, or dbt Semantic Layer experience is especially relevant. \n

• SaaS experience is strongly , especially working with Salesforce and supporting revenue operations, customer success, product usage, adoption, retention, renewals, or ARR reporting., You must be authorized to work full-time in the United States without current or future employer sponsorship.

Today, critical data lives across Sales, Finance, Customer Success, Product, and other systems. There is not yet a centralized warehouse, shared metric definitions, or a reliable semantic layer. This person will help change that.

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You will own the technical foundation for trusted reporting and decision-making: helping shape the stack, standing up the warehouse and transformation layer, bringing in priority source data, establishing governed metrics and semantic models, and creating a scalable BI strategy.

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Snowflake is the likely warehouse direction, and Omni is the likely BI platform, but neither is fully locked. We want someone who has done this before and can bring strong, practical judgment on architecture, tooling, and sequencing-not someone looking to inherit a fully defined environment.

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This is a high-ownership, greenfield build. You will report directly to the Revenue Strategy and Analytics leader, work in a hands-off environment, and have the autonomy to take a project from ambiguity to a well-executed outcome.

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What You’ll Do

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• Help define and implement the modern analytics stack: warehouse, ingestion/ELT, transformation, testing, documentation, governance, BI, and semantic-layer tooling. \n

• Lead the buildout of a centralized cloud warehouse-likely Snowflake-and create reliable pipelines and production-grade models across Salesforce, Finance, Customer Success, Product, and other core systems. \n

• Establish a governed semantic layer with trusted metric definitions, reusable dimensions, appropriate access controls, and business-friendly models for reporting and self-service analytics. \n

• Shape and implement the BI strategy, likely using Omni or a comparable modern platform. \n

• Build durable models for pipeline, bookings, ARR, renewals, customer adoption, account health, and the other metrics that run a SaaS business. \n

• Create the foundation for product analytics, including product-usage data, event tracking, and event-level analysis. \n

• Partner directly with business leaders to turn ambiguous questions into trusted data products, while building an AI-ready foundation for future natural- and AI-assisted reporting. \n

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• High ownership, sound judgment, and strong stakeholder skills. You can clarify ambiguity, make thoughtful technical recommendations, communicate directly, and drive work to completion without close day-to-day management. \n

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A Strong Plus

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• You have selected or implemented a modern data stack in a greenfield or high-growth environment. \n

• You have direct Snowflake and/or Omni Analytics experience. \n

• You have worked with product-event data, product instrumentation, feature adoption, or usage analytics. \n

• You have integrated data from Salesforce, customer-success tools, billing platforms, product-event tools, support systems, marketing automation, or finance systems. \n

• You have built semantic layers or governed data products that support self-service BI, natural- querying, or AI-assisted analytics. \n

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Who This Is Not For

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This is not a dashboard-maintenance or Tableau-heavy role. It is not a pure data-science or machine-learning role, either.

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