Director, Product Management - Data & Analytics

Role summary 

As Director of Product Management for Data & Analytics, you will lead the development and lifecycle management of Brightree’s data products from operational reporting and analytics to governed data extracts, Data-as-a-Service, and insight monetization. You will own the vision, roadmap, and outcomes for our data platform (lakes/warehouses/marts), analytics experiences, and AI-enabled use cases, ensuring teams have the tools, capabilities, and insights to make data-driven decisions. This is a hands-on product leadership role: you’ll partner closely with Customers, Business Leaders, Data Engineering/Analytics Engineering, and Data Science to translate real problems into lovable products, ship iteratively, and measure impact. You are fully accountable for product direction and outcomes, enabling autonomous, multidisciplinary product teams and a disciplined lifecycle from launch through adoption, working horizontally across Brightree and ResMed brands. 

Competencies and Responsibilities: 

Set strategy & roadmap 

• Define a multi-year product strategy for data & analytics, including self-service BI, governed semantic models, and AI-assisted analytic experiences. 

• Prioritize outcomes (adoption, decision quality, time-to-insight) and maintain a transparent, KPI-driven roadmap. 

Build the platform & experiences (with Engineering) 

• Partner with data/analytics engineering to deliver scalable pipelines and large-scale stores (data lake, warehouse, marts) that back productized analytics. 

• Specify product requirements for models, metrics, lineage, and performance SLAs; ensure reliability, security, and cost efficiency. 

Own governance as a product 

• Stand up a pragmatic data governance framework accuracy, consistency, security, access, privacy embedded in product workflows (not side docs). 

• Drive standard definitions for KPIs and event models; publish contracts and change-management playbooks. 

Lead AI adoption (applied, not academic) 

• Evaluate and productize AI-powered data & analytics tools (e.g., natural-language insights, auto-classification, anomaly detection), with human-in-the-loop guardrails. 

• Build the integrated data foundation that enables AI-driven experiences across functions. 

Customer & stakeholder leadership 

• Run discovery with customers and internal stakeholders; turn problems into clear PRDs, success metrics, and experiments. 

• Regularly engage executives and major customers; negotiate trade-offs and influence senior leaders on matters of significance. 

Team leadership & operating cadence 

• Hire, mentor, and lead PMs, TPMs, and Product Operations (and matrixed analysts) to high performance. 

• Establish a product operating rhythm: quarterly planning, monthly business reviews, launch checklists, and post-launch measurement. 

Qualifications & experience 

• Bachelor’s in Computer Science, Data/Analytics, or related field. 

• 12+ years in Data & Analytics product management (or adjacent leadership) delivering platform and analytics products; supply chain or finance domain experience a plus. 

• Working literacy with Snowflake, SQL, dbt, Python and modern BI able to collaborate deeply with engineering and analytics teams (no daily coding required). 

• Evidence of a track record of building self-service analytics and governed data products that drive adoption and measurable business value. 

• Proven success leading non-exempt teams, developing Product Managers/Technical Product Managers, and leading in a matrix environment. 

• Demonstrated ability to work through ambiguity, make tough calls, and lead through change with end-to-end ownership. 

• Executive-level communication: translate complex technical concepts into crisp narratives and decision-ready options; strong stakeholder management and negotiation skills. 

• Track record applying AI/ML pragmatically in analytics workflows (e.g., natural-language querying, forecasting, anomaly detection) with attention to governance and risk. 

• History of operating at enterprise scale; looks beyond existing methodologies to define and solve complex, cross-org problems. 

• Enterprise collaborator: aligns Product, Commercial, and Operations; communicates crisply at the executive level. 

• Team builder: attracts and develops cross-functional talent; leads decisively under pressure.