Senior Manager, Data Analytics

Positively disrupting an industry that has not seen any innovation in over 50 years, Tekion challenges the paradigm with the first and fastest cloud-native automotive platform that includes the revolutionary Automotive Retail Cloud (ARC) for retailers, Automotive Enterprise Cloud (AEC) for manufacturers and other large automotive enterprises and Automotive Partner Cloud (APC) for technology and industry partners. Tekion connects the entire spectrum of the automotive retail ecosystem through one seamless platform.

The transformative platform uses cutting-edge technology, big data, machine learning, and AI to seamlessly bring together OEMs, retailers/dealers and consumers. With its highly configurable integration and greater customer engagement capabilities, Tekion is enabling the best automotive retail experiences ever. Tekion employs close to 3,000 people across North America, Asia and Europe.

The Senior Manager, Analytics leads a high-performing team of Data Product Managers to deliver data-driven insights, AI initiatives and analytics products that accelerate business growth and support critical decision-making. This role partners closely with stakeholders across Finance, Sales, Marketing, People, Professional Services and Engineering to identify AI opportunities, prioritize initiatives, and deliver analytics solutions for core business processes.

• Strategy and Stakeholder Partnership

  Develop and own the Analytics and Enterprise AI strategy and roadmap for key business areas, ensuring alignment with enterprise data management and AI objectives.

  Collaborate with senior business stakeholders to scope high-impact problems, define success metrics, and co-create analytics roadmaps that inform product development and operations.

  Champion data-driven decision-making by promoting consistent KPIs, self-service analytics tools, and evidence-based recommendations at the executive level.

• Team Leadership and Development

  Lead and expand a team of Data Product Managers, including hiring, coaching, performance management, and career development.

  Foster a collaborative, inclusive environment that encourages innovation, experimentation, and continuous improvement in analytics tools, methods, and processes.

• Core Analytics & Insights

  Oversee the design, execution, and delivery of advanced analytics, predictive models, and data products using modern cloud-based data platforms.

  Guide Data Product Managers in building reusable semantic layers, dashboards, and ML-powered insights tailored to stakeholder needs.

  Ensure analytical rigor through data validation, peer reviews, and comprehensive documentation; translate complex findings into clear, actionable recommendations for non-technical audiences.

• Data as a Product

  Champion a "data as a product" mindset by partnering with domain owners to deliver trusted, well-documented datasets with clear ownership and defined SLAs.

  Drive adoption of an enterprise data catalog to enable self-service data discovery, document data lineage, and provide transparency into data assets across the organization.

  Own the enterprise business glossary in partnership with business stakeholders, ensuring consistent definitions and semantic alignment across reports, metrics, and data products.

• Data Quality & Profiling

  Lead data profiling initiatives to assess source data for completeness, accuracy, consistency, and fitness for analytics and AI use cases.

  Define and enforce data quality rules, thresholds, and scorecards across critical data domains; establish remediation workflows to address issues before they impact downstream consumers.

  Define success criteria, data dependencies, and certification standards within owned functional domains.

• AI, Machine Learning & Generative AI

  Design data ecosystems that support advanced analytics, machine learning, and AI-driven insights—ensuring structured and unstructured data (including documents and logs) are accessible, reliable, and actionable.

  Demonstrate hands‑on experience with AI agents and generative AI, including building and integrating conversational bots, autonomous agents, and generative AI models into enterprise workflows.

  Eval…