Responsibilities
Leadership & Team Management
- Hire, develop, and lead a high-performing team of Analytics Engineers
- Foster a culture of technical excellence, ownership, continuous learning, and collaboration
- Provide coaching, career development, and regular performance feedback
- Establish team goals, operating rhythms, and execution processes that align with company priorities to deliver business impact
Analytics Engineering Strategy
- Define and execute the roadmap for analytics engineering, data modeling, semantic layers, and analytics infrastructure
- Build scalable dimensional models and curated datasets that enable trusted reporting and advanced analytics
- Drive adoption of analytics engineering best practices including testing, documentation, version control, CI/CD, and code review
- Own data quality initiatives, observability, lineage, and governance across the analytics ecosystem
- Continuously improve developer productivity and platform scalability
Cross-Functional Partnership
- Partner with peers on the Data team and business stakeholders to understand evolving analytical needs and translate them into scalable data products
- Collaborate with Data Engineering to improve data pipelines, ingestion, orchestration, and warehouse performance
- Work alongside Product Analytics & Data Science to enable experimentation, machine learning, and advanced analytics
- Support Finance and Executive Leadership with trusted metrics and executive reporting
- Help establish company-wide metric definitions and ensure consistency across teams
Technical Leadership
- Set standards for data modeling, transformation, documentation, and testing
- Guide architectural decisions for the analytics stack and evaluate new technologies
- Ensure analytics infrastructure scales with rapid business growth
- Review technical designs and mentor engineers through complex implementation challenges
- Champion automation, reliability, and engineering best practices throughout the data organization
- Thinks strategically while remaining execution-oriented, making pragmatic trade offs between speed, scalability, and technical debt
- Builds trust through transparency and strong communication, delegating to and developing future technical leaders
- Thrives in fast-moving, ambiguous environments and helps others navigate change
Requirements
- 11+ years of experience in analytics engineering, business intelligence, data engineering, or related fields
- 3+ years managing high-performing technical teams, growing and developing people
- Deep expertise with SQL and modern analytics engineering practices
- Experience building analytics platforms using DBT, Snowflake, Airflow or similar orchestration tools
- Familiarity with Git and CI/CD workflows and BI platforms
- Strong understanding of dimensional modeling, semantic layers, and data warehousing concepts
- Experience defining data governance, testing, and data quality frameworks
- Excellent stakeholder management and communication skills
- Demonstrated ability to influence technical strategy across multiple organizations
Nice to Have
- Experience partnering with accounting/close the books procedures at a public company
- Experience managing audit processes and governance programs is a plus
- Experience at a high-growth SaaS or technology company
- Experience scaling analytics organizations through rapid company growth
- Familiarity with event-driven data architectures and product analytics
- Experience supporting experimentation platforms and machine learning initiatives
- Knowledge of metrics governance and executive KPI frameworks