Director, Data Products & Analytics Strategy

ROLE OVERVIEW

As Director, Data Products and Analytics Strategy, you will lead the strategy and delivery of trusted, full-stack data products across GTM, Finance, Customer, Product, Marketing, and other enterprise domains - from well-governed dbt data models and semantic metrics through to decision-ready Tableau dashboards and AI-ready analytical assets.

This is a senior, hands-on role based in the San Francisco Bay Area, with clear technical expectations. You will work with senior business and functional leaders to frame business questions, clarify requirements, align metrics, and sequence the enterprise analytics roadmap. You will also personally build and review production-grade dbt models, complex SQL and Python analysis, and dashboards at the same standard expected of our strongest data-product builders. You will work closely with the Analytics Engineering, BI, Governance, and AI/ML leaders across our Enterprise Data team and SME Domain Experts, leading through influence and connecting priorities to delivery 

The right candidate combines technical depth, sound judgement, and the ability to work effectively with senior leaders. You can open a dbt project, trace a metric to its source, write the SQL or Python needed to resolve an issue, build a useful dashboard, and explain the trade-offs and recommendations clearly to a senior business audience.

We are looking for someone based in the Bay Area who can be in our San Francisco office on Wednesdays to be a close collaborator with Business Applications ,GTM Tech and Marketing leadership based in the region. 

KEY RESPONSIBILITIES

•    Define and maintain a cross-domain data products and analytics strategy spanning GTM, Finance, Customer, Product, Marketing, and other priority business areas, translating enterprise goals into a sequenced, outcome-focused roadmap
•    Work with senior business and functional leaders to frame business questions, translate ambiguous requirements into clear metric and product specifications, and align on practical measures of success
•    Design, build, and review production-grade dbt data models across staging, intermediate, and mart layers following SolarWinds modelling standards and creating consumption-ready, well-tested data products
•    Partner with domain delivery leads each quarter to jointly identify the highest-value, highest-complexity initiatives, and take a direct, hands-on build role on that critical subset — reinforcing delivery capacity rather than creating a parallel workstream
•    Use advanced SQL and Python for transformation, data quality, automation, exploratory analysis, custom dbt macros, and performance investigation — remaining hands-on enough to validate solutions in the codebase
•    Build or oversee high-quality Tableau dashboards and self-serve analytics assets from requirements through stakeholder sign-off, ensuring the experience is performant, understandable, and grounded in governed models and metrics
•    Drive alignment of cross-domain metrics, semantic definitions, lineage, and documentation with business owners and Governance, creating a trusted analytical language without taking ownership of source-system processes
•    Coordinate priorities, dependencies, and delivery standards across Analytics Engineering, Governance, and AI/ML, partnering with functional leaders to turn strategy into shipped products
•    Champion engineering and product discipline through dbt tests, CI/CD, Git workflows, observability, delivery SLAs, adoption measurement, and the retirement of redundant or low-value reporting
•    Work effectively with San Francisco / Bay Area-based leaders, communicate progress and trade-offs clearly, enable self-service analytics, and mentor practitioners across the distributed Enterprise Data team. Work with the team in-office approximately 1 day per week, generally on Wednesdays, but with some flexibility around frequency and day of week.

REQUIRED SKILLS & EXPERIENCE

•    7+ years of experience across analytics engineering, business intelligence, data products, analytics strategy, or related data roles, with experience leading cross-functional work and influencing senior stakeholders
•    Production-grade dbt experience (dbt Core or dbt Cloud) — you have designed and maintained multi-layer models at scale, written macros, implemented tests, and established reusable modelling patterns
•    Expert SQL skills — complex analytical queries, window functions, CTEs, aggregations, dimensional modelling, metric logic, and query performance awareness
•    Strong Python proficiency for analytics and data engineering use cases — data wrangling, automation, testing, custom tooling, exploratory analysis, or production workflows
•    Demonstrated ability to build governed, performant, and user-friendly Tableau dashboards or equivalent BI products from scratch and explain design decisions to executives and business users
•    Experience with a modern cloud data warehouse, preferably BigQuery, including materialisation, partitioning, clustering, cost, and performance trade-offs
•    Strong understanding of data modelling and analytics architecture — conformed entities, marts, star schema, slowly changing dimensions, semantic layers, metric normalisation, and lineage
•    Experience with Git, branch-based development, code review, and CI/CD in a data context — you apply software engineering discipline to analytics code
•    Proven ability to lead senior-stakeholder discovery and requirements conversations, communicate technical trade-offs clearly, and convert business needs into an actionable data-product brief
•    Experience setting priorities across multiple domains and delivery teams, resolving conflicting requirements, and building alignment without relying solely on formal authority
•    Practical experience using AI tools such as Claude, Gemini, GitHub Copilot, or similar to accelerate analysis, coding, documentation, and exploration. You apply sound engineering judgement to generated output: understanding and reviewing the code, validating results against requirements and source data, adding appropriate tests, and considering security, privacy, performance, and maintainability before anything reaches production

NICE TO HAVE

•    Hands-on MetricFlow or dbt Semantic Layer experience in a production environment
•    Experience in a SaaS or recurring-revenue business — ARR, bookings, pipeline, conversion, churn, renewals, expansion, and NRR metrics
•    Experience working with GTM, Finance, Customer, Product, and Marketing data, including Salesforce, NetSuite, Gong, Zoom, product-usage, or support data
•    Exposure to Dataplex, Fivetran, or similar data cataloguing, ELT, observability, and data-quality tooling
•    Experience rationalising reporting portfolios, increasing self-service adoption, and measuring the business value of data products
•    Experience working in a distributed, multi-location data organization and partnering with private-equity sponsors, board-facing teams, or other senior operating leaders