Senior Manager of Analytics

Our client's Analytics team builds the trusted data that the company runs on. That includes revenue and billing data that drives our monthly close, the metrics our leadership and board use, the self-service tools GTM and Product use every day, and the semantic layer that lets AI agents answer questions correctly.

As Senior Manager of Analytics, you'll lead the team and do a lot of the building yourself. You'll own our dbt models, Snowflake warehouse and Omni semantic layer. You'll make sure financial data is accurate and on time each month and work with Finance, GTM and Product to turn their questions into reliable data products. You'll report to the CFO, manage a small team of analytics engineers and set the technical bar for how we build. All positions at our client are fully remote.

Primary duties
Build and own the data model. Design, write and review production dbt models in Snowflake, following software engineering best practices (version control, testing, code review, CI).
Own the semantic layer. Keep Omni topics, metric definitions and documentation accurate and consistent so people and AI agents get the same answer to the same question.
Drive data quality. Define and track data quality standards and test coverage for top-priority models. Find root causes and fix them upstream with Data Engineering and Product.
Enable self-service. Build dashboards, tools and AI-assisted workflows so Finance, RevOps, GTM and Product can answer their own questions, and train teams to use them.
Partner with stakeholders. Work with Finance, RevOps, GTM and Product leaders to scope needs, do exploratory analysis and turn recurring asks into lasting data products.
Lead and grow the team. Manage and coach analytics engineers. Run intake and prioritization, set the roadmap with the CFO and hire when we add headcount.
Build AI-first. Use AI tools to speed up modeling, querying, testing and documentation, and maintain the skills, prompts and evals behind our internal data agent.

What We'll Love About You
6–10 years in analytics, analytics engineering or BI, including 2+ years leading or mentoring other analysts or engineers (formal or as a tech lead)
Still hands-on: expert SQL (window functions, complex joins, semi-structured data) and production dbt experience in a cloud warehouse (Snowflake preferred; BigQuery or similar fine)
Experience owning financial or revenue data: billing, revenue recognition, ARR/NDR or usage-based revenue, ideally supporting a monthly close
Strong opinions on data modeling (dimensional, layered dbt projects) and data quality practices
Experience building semantic layers and self-service tools in a modern BI platform (Omni, Looker, Hex, Tableau)
Uses AI tools (Claude, Codex, Cursor, dbt Copilot) to build faster, and has a view on making data AI-ready
Comfortable prioritizing competing asks from senior stakeholders and explaining tradeoffs clearly
Clear writer who documents by default
High-growth or early-stage SaaS experience strongly preferred
Python and orchestration tools (Airflow, Prefect, Dagster) a plus

Skills

6–10 years in analytics, analytics engineering or BI with 2+ years leading or mentoring other analysts or engineers, expert SQL including window functions and complex joins, production dbt experience in Snowflake, and experience owning financial or revenue data including billing, revenue recognition, ARR/NDR or usage-based revenue.

High-growth or early-stage SaaS experience, Python and orchestration tools such as Airflow, Prefect or Dagster, and experience using AI tools like Claude, Codex, Cursor or dbt Copilot to build faster.