Director, Analytics Engineering

About the Role

We are seeking an experienced Director of Analytics to define and execute the vision for a modern enterprise analytics ecosystem that serves both internal stakeholders and external customers at scale. This is a unique opportunity for a builder and strategist who has personally delivered production-grade analytics solutions and is passionate about transforming data into competitive advantage. You'll lead a talented analytics engineering team while remaining deeply involved in architecture, platform design, governance, and technical decision-making.

The Director of Analytics will own the strategy, architecture, and execution of a large-scale analytics platform that supports reporting, self-service analytics, data-driven decision-making, and embedded analytical experiences. This is not a management-only role; we are looking for a technical leader who has built data pipelines, designed semantic models, developed client-facing analytics products, and understands the challenges of delivering reliable analytics in complex environments.

Responsibilities

• Analytics Platform Strategy & Delivery
  • Define and execute a long-term analytics and business intelligence roadmap.
  • Lead the end-to-end delivery of data products across ingestion, warehousing, modeling, visualization, and embedded analytics.
  • Design scalable, client-facing analytics experiences and self-service reporting capabilities.
  • Establish standards for data lifecycle management, governance, and platform reliability.
  • Ensure analytics products align with business objectives and user needs.
• Technical Leadership
  • Serve as the senior authority on analytics architecture, data modeling, warehouse design, and business intelligence strategy.
  • Provide hands-on guidance on data pipelines, performance optimization, cloud architecture, and cost management.
  • Champion modern analytics engineering practices including CI/CD, version control, testing, automation, and infrastructure-as-code.
  • Drive innovation while balancing scalability, maintainability, and operational excellence.
  • Evaluate emerging technologies and determine where they add meaningful value.
• Team Leadership & Development
  • Build, mentor, and lead a high-performing analytics engineering organization.
  • Foster a culture of ownership, technical excellence, collaboration, and continuous improvement.
  • Recruit top-tier analytics and data engineering talent.
  • Establish career development frameworks, technical mentorship programs, and succession planning.
  • Partner closely with engineering, product, operations, and business leaders.
• Data Governance & Operations
  • Implement governance frameworks covering security, access controls, compliance, lineage, quality, and observability.
  • Define and monitor service level expectations for data availability, freshness, and platform performance.
  • Establish operational best practices that ensure reliability and trust in analytics assets.
  • Build monitoring and alerting capabilities across the analytics ecosystem.
• Executive & Stakeholder Partnership
  • Translate business strategy into scalable analytics capabilities.
  • Communicate complex technical concepts to executive and non-technical audiences.
  • Act as a trusted advisor on analytics strategy, data architecture, and reporting solutions.
  • Influence cross-functional decision-making through data and insight.

Requirements

• Leadership Experience
  • 10+ years of experience in analytics engineering, data engineering, business intelligence, or related technical disciplines.
  • 5+ years leading and developing high-performing analytics or data engineering teams.
  • Proven success delivering enterprise-scale analytics platforms and data products.
  • Strong experience recruiting, mentoring, and retaining technical talent.
  • Demonstrated ability to balance strategic leadership with hands-on technical involvement.
• Technical Expertise
  • Deep experience with modern cloud-based data warehousing and analytics architectures.
  • Advanced SQL expertise, including performance tuning and large-scale data modeling.
  • Strong knowledge of business intelligence and visualization platforms such as Looker, Tableau, or Power BI.
  • Experience with semantic modeling, self-service analytics, and governed reporting environments.
  • Expertise in Python for data engineering, automation, and analytics workflows.
  • Familiarity with data transformation, orchestration, and pipeline development tools.
  • Understanding of modern software engineering practices including Git, CI/CD, DevOps, and infrastructure automation.
  • Experience working across cloud environments such as AWS, Azure, and/or GCP.
• Governance & Performance
  • Experience implementing enterprise data governance frameworks.
  • Knowledge of security, compliance, data quality, observability, and monitoring practices.
  • Strong background in system optimization, scalability, and performance management.
• Communication & Leadership Style
  • Outstanding communication and stakeholder management skills.
  • Ability to influence executives, technical teams, and business leaders alike.
  • Strategic thinker with a builder's mindset.
  • Comfortable operating in fast-changing environments and making informed decisions amid ambiguity.
  • Passionate about using data to drive measurable business outcomes.

Preferred Qualifications

• Experience building customer-facing or embedded analytics products.
• Expertise supporting multi-tenant analytics environments.
• Knowledge of infrastructure-as-code and containerization technologies.
• Exposure to AI and machine learning-enabled analytics solutions.
• Advanced degree in Data Science, Computer Science, Mathematics, Engineering, or a related quantitative discipline.