Sr. Director, Enterprise Data & Analytics

Vetsource • Remote - NY, ON

13d • $190,265 - $240,000 • Remote

About The Position

The Senior Director, Enterprise Data leads Vetsource's enterprise data organization and is accountable for making data a trusted, high-value business asset to drive product innovation and business performance. This role brings together data engineering, analytics, MLOps, AI engineering, and data services under a common strategy and operating model. Working closely with business leaders, product, security, and technology teams, the Senior Director, Enterprise Data translates business priorities into governed data products, scalable platforms, meaningful insights, and AI capabilities. The role is responsible for measurable improvements in data quality, adoption, and business value for associates, customers, and industry partners.

Requirements

• 12+ years of progressive experience across data engineering, analytics, and data platforms
• 8+ years of leadership experience managing multidisciplinary teams and leaders.
• Proven track record in delivering production AI/ML capabilities, including assessing data readiness, enforcing AI governance (access controls, audit trails), and managing MLOps/LLMOps.
• Demonstrated experience defining and executing an enterprise data strategy or broad data transformation with measurable business outcomes.
• Strong and prior hands on data engineering background, including experience with modern cloud data platforms, data modeling, batch and near real time streaming platforms like Kafka, schema registries, APIs and integration patterns, testing, observability, and production operations.
• Experience leading analytics and business intelligence capabilities, including governed metrics, semantic models, dashboards, experimentation, or advanced analytics.
• Experience establishing data governance, catalog, lineage, quality, access, ownership, and stewardship practices in partnership with business leaders.
• Strong business and financial acumen, including experience managing budgets, vendors, investment tradeoffs, and capacity planning.
• Ability to communicate complex technical and analytical topics clearly to executive, business, customer, and technical audiences.
• Demonstrated ability to lead through influence, build alignment across functions, and convert ambiguous opportunities into focused plans and delivered results.

Nice To Haves

• Experience with cloud data and AI services, modern data warehouses or lakehouses, transformation and orchestration tools, event platforms, BI tools, and data catalogs.
• Experience building data products or commercial data services for external customers and partners.
• Experience in veterinary health, animal health, pharmacy, healthcare, ecommerce, or another regulated, data-intensive industry.
• Bachelor's or advanced degree in computer science, engineering, data science, mathematics, statistics, information management, economics, or a related discipline, or equivalent practical experience.

Responsibilities

• Own and execute the enterprise data strategy in alignment with company priorities, product strategy, and technology roadmaps.
• Lead the Data as a First Class Citizen initiative, establishing the operating model, standards, investment priorities, and measures required to treat data as a durable enterprise asset.
• Partner with executive and business leaders to identify the highest-value data opportunities, clarify tradeoffs, and translate strategy into sequenced roadmaps with clear outcomes.
• Define and report enterprise data health and value measures, including quality, timeliness, reliability, accessibility, adoption, and business impact.
• Lead analytics and business intelligence teams that develop trusted metrics, analytical models, dashboards, and decision-support products for internal stakeholders and external customers.
• Adopt a data product approach for priority business domains, with defined customers, accountable business and technology owners, quality expectations, service levels, documentation, and adoption measures.
• Partner with business teams to define critical data domains and common metrics so teams can make decisions using consistent, well-understood information.
• Ensure analytical work addresses a clear business decision or workflow and produces measurable value, not simply reports or dashboards.
• Develop the data and platform foundations required for AI-powered products, predictive analytics, intelligent automation, and generative AI use cases.
• Partner with product, engineering, security, privacy, legal, and business leaders to evaluate and deliver AI use cases with appropriate controls for data access, quality, privacy, safety, traceability, and monitoring.
• Enable associates and customers to access approved data and insights through governed conversational interfaces and AI assistants, while preserving metric consistency, permissions, and source traceability.
• Establish practical standards for model and prompt lifecycle management, evaluation, monitoring, human oversight, and MLOps or LLMOps where applicable.
• Build data and AI literacy across the organization through education, reusable patterns, and close partnership with business teams.
• Create a federated governance model that assigns business and technology ownership for critical data and establishes clear decision rights and stewardship responsibilities.
• Oversee the enterprise data catalog, business glossary, lineage, quality rules, access policies, retention practices, and issue-management processes.
• Partner with security, privacy, compliance, and legal teams to ensure data and AI capabilities meet contractual, regulatory, ethical, and company requirements.
• Build trust by making data quality and ownership transparent and by ensuring material data issues are prioritized, communicated, and resolved.
• Serve as a trusted advisor to leaders across the company, helping them frame business questions, understand data limitations, and use evidence to make better decisions.
• Create a transparent intake and prioritization process that balances strategic initiatives, customer commitments, platform health, regulatory needs, and operational support.
• Manage divisional objectives, service metrics, budgets, vendor relationships, and capacity plans; communicate progress, dependencies, and risks clearly to executive stakeholders.
• Promote strong product management and engineering practices that improve delivery speed, quality, accountability, and customer experience.
• Lead a multidisciplinary organization that may include managers and individual contributors across data engineering, integration, analytics, business intelligence, AI engineering, MLOps, and data product development.
• Set clear goals and decision rights, manage performance, and hold leaders accountable for business outcomes, platform reliability, and delivery commitments.
• Recruit, develop, coach, and retain high-performing teams; build succession plans and strengthen technical, product, analytical, and leadership capabilities.
• Create an inclusive culture of ownership, curiosity, constructive challenge, continuous learning, and responsible innovation.
• Delegate effectively, remove organizational blockers, and help teams make sound decisions close to the work.

Benefits

• Competitive pay and benefits including medical, vision, dental, and life insurance
• Employee Assistance Program
• Pet insurance and Virtual vet care
• PTO, Holidays, Floating Holidays, and Volunteer Day
• Retirement Savings Plan (401k/ RRSP) with employer matching program
• Paid parental leave
• Flexible scheduling and remote work where possible
• The opportunity to join one of our Associate Resource Groups, and fun company events!

What This Job Offers

• Job Type: Full-time
• Career Level: Director
• Education Level: Associate degree