Vice President of Data
Skills
Software As A ServiceAdoptionContextData AnalyticsData StrategiesDimensional ModelingElectrical Wiring
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- 12+ years in data engineering analytics engineering BI data architecture data products or related disciplines
- 5+ years leading data teams including managers or senior technical leaders
- Proven success transforming a data function at a growing SaaS or technology company
- Deep experience with Snowflake dbt Fivetran and Sigma
- Strong understanding of dimensional modeling semantic layers entity resolution master data golden records data contracts lineage observability and quality engineering
- Experience integrating and governing data from Salesforce and other core SaaS systems
- Ability to establish governed business metrics and resolve cross-functional disputes
- Strong commercial understanding of recurring revenue business models and SaaS operating metrics
- Experience designing data products for executive operational analytical and machine consumers
- Experience supporting planning forecasting customer lifecycle analysis go-to-market analytics financial reporting and product analytics
- Personally built and shipped at least one production AI agent or agentic workflow
- Hands-on technical capability to write and review SQL inspect dbt projects evaluate models troubleshoot pipelines and prototype solutions
- Exceptional written and verbal communication
- Ability to influence senior executives and drive difficult cross-functional changes
Nice to have
- Visionary
- Transformational
- Commercially fluent
- Technically credible
- Operationally grounded
- Agent-fluent
- Product-minded
- Politically mature
- Truth-seeking
- Principled
- Headstrong
- Collaborative
Day to day
- Lead a company-wide data transformation and establish data as a strategic operating advantage.
- Define and execute the enterprise data strategy using governed source-of-truth systems and trusted golden records.
- Partner across Product Engineering Sales Marketing Finance Customer Success and Operations to improve decisions forecasting and accountability.