Senior Manager - Tech Strategy - Data Products

Responsibilities

• Lead Data Products
• Own the vision, strategy, roadmap, and lifecycle for a portfolio of ETS workforce data products, ensuring they deliver measurable business value and enable analytics, AI, and intelligent decision-making.
• Serve as the voice of the customer, translating business needs into scalable, trusted, and reusable data products
• Serve as a key liaison to Analytics Engineering, connecting data product strategy and business requirements with analytical data models, capabilities, and consumption needs to ensure products are analytics-ready and reusable at scale
• Drive Data Product Strategy & Prioritization
• Lead product discovery and define product priorities based on customer insights, business value, enterprise objectives, and market trends.
• Develop business cases, define success metrics, and continuously evolve the product roadmap based on adoption, customer feedback, and changing business needs
• Partner to Deliver Outcomes
• Partner with Data Engineering, Architecture, Data Governance, and Program Management to ensure product priorities are successfully delivered while balancing business needs, technical feasibility, and enterprise standards
• Act as the connective point between customers, Analytics Engineering, and Data Engineering to align on requirements, data models, definitions, dependencies, and priorities across the end-to-end data product lifecycle
• Drive adoption and value realization by measuring product performance and identifying opportunities for continuous improvement
• Shape Enterprise Data Strategy
• Influence TBE & ETS data strategy by identifying opportunities to expand and modernize the data product portfolio
• Build trusted partnerships across Business and Technology, champion a product mindset, and position data as a strategic enterprise asset that accelerates AI, analytics, and digital innovation
• Partner with Analytics Engineering and other data and technology teams to identify opportunities for reusable data models and capabilities that accelerate analytics, AI, and intelligent decision-making across the enterprise
• Champion a product mindset and promote data as a strategic enterprise asset

Qualifications

• Education & Knowledge :
• MBA or equivalent qualification preferred; Bachelor’s degree in Business, Computer Science, Engineering, Data Science, or a related field preferred
• Strong understanding of data product management principles, product lifecycle management, and customer-centric product development
• Knowledge of modern data ecosystems, including cloud data platforms, APIs, analytical data modeling, semantic layers, metadata, data governance, and data quality principles
• Understanding of how data products are modeled, transformed, and consumed for analytics and reporting, with sufficient technical fluency to effectively partner with Analytics Engineering and Data Engineering teams
• Understanding of AI-enabled products, machine learning, Generative AI, and how trusted data products enable intelligent decision-making and AI-driven experiences
• Knowledge of AI governance, responsible AI principles, and data privacy considerations to support scalable and compliant AI adoption Work Experience:
• Experience defining product vision, strategy, and roadmaps for enterprise data products, platforms, or digital capabilities
• Experience identifying business opportunities and translating customer needs into scalable data product strategies that deliver measurable business value
• Experience developing business cases, investment recommendations, product value propositions, and success metrics to support strategic decision-making
• Demonstrated ability to leverage data products to enable analytics, AI, and intelligent automation across the enterprise
• Experience using customer insights, product analytics, and market trends to prioritize product investments and guide product evolution
• Experience partnering with Analytics Engineering and Data Engineering teams to translate business and analytical needs into scalable, reusable data products and capabilities
• Proven ability to influence senior stakeholders and build alignment across Business, Technology, Analytics Engineering, Data Engineering, Architecture, Data Governance, and Analytics teams
• Experience leading cross-functional initiatives within complex, matrixed organizations and driving outcomes through influence rather than direct authority
• Experience evaluating emerging technologies, AI capabilities, and industry trends to identify opportunities for innovation and competitive advantage
• Strong analytical and strategic problem-solving skills with the ability to translate complex business challenges into product opportunities
• Experience working in Agile product environments and partnering with Engineering teams to successfully deliver strategic product outcomes

About Company

Company