Senior Technical Product Manager - Data Platform

We are seeking a Senior Product Manager to drive the strategic evolution of our Core Data Platform. In this role, you will bridge the gap between high‑level data vision and tactical execution, transforming complex datasets into high‑growth product capabilities. Acting as a Product Catalyst, you will own the end‑to‑end data lifecycle by collaborating with Data Engineering, Analytics, and Design to ship data products that customers find indispensable. We are looking for a product leader comfortable defining 10x growth strategy for data accessibility, insights and data products while ensuring the flawless delivery of platform scalability. What You’ll Do Data Insight & Platform Strategy Market Intelligence: Synthesize deep customer empathy with rigorous analysis of data trends and the competitive landscape to drive informed platform and tool decisions. Strategic Direction: Uncover and validate data "whitespace" emerging analytics trends, and growth levers to inform our data platform and data products direction. Enterprise Portfolio Strategy: Lead the data platform’s expansion across a complex multi‑product portfolio, influencing the integration roadmap for 10+ products to maximize collective business value and platform adoption. Platform Vision: Define and evangelize an aspirational vision for our Data Platform, aligning it with long‑term company goals and market opportunities. Data Contract Excellence: Identify and validate whitespace in our data architecture, establishing data contracts to ensure high‑quality, reliable, and decoupled data exchanges between producers and consumers. Roadmap & Backlog Management Strategic Alignment: Translate high‑level strategy into a high‑impact roadmap that rigorously balances customer value, business ROI, and technical constraints like latency and throughput. Operational Rigor: Author and maintain a high velocity backlog characterized by precision‑engineered epics and user stories for data pipelines, APIs, stream‑based processing and semantic data modeling to unify our product data. Technical Trade‑offs: Execute complex trade‑off decisions that prioritize speed to market without compromising long‑term platform scalability or data consistency. Product Discovery & Experience Optimization Collaborative Design: Partner with Design and Business Unit Product Managers to prototype and rapidly validate data‑as‑a‑product solutions that solve complex user problems. Experimentation Culture: Spearhead an experimentation culture, utilizing A/B testing and performance benchmarking to relentlessly optimize data latency to optimize data‑driven user journeys powered by the data platform. Synthesis: Merge qualitative user feedback with quantitative behavioral data to drive high‑conviction product decisions. Cross‑Functional Execution Engineering Partnership: Work in lockstep with Data Engineering to translate complex schema requirements and stream‑processing logic into shippable code, maintaining a focus on quality and on‑time delivery. Stakeholder Synchronization: Socialize priorities and scope across the organization, ensuring cross‑functional stakeholders are unified on data quality standards and integration patterns. Radical Accountability: Act as the ultimate point of accountability for the success, quality, and impact of every product increment, from pipeline stability to data accuracy. Product Team Partnership: Forge deep strategic alliances with business unit leaders to co‑author data adoption requirements, ensuring the platform roadmap is prioritized to maximize portfolio‑wide customer value. Go‑To‑Market & Performance Commercial Synergy: Partner with Product Marketing to architect compelling positioning for our platform's real‑time insights and advanced analytics capabilities. Enablement: Empower Sales and Customer Success with deep product intelligence to accelerate adoption of our data‑driven features. Growth Metrics: Define and measure a robust set of success metrics including platform adoption, pipeline reliability, and time‑to‑insight to quantify product impact. Continuous Optimization: Extract actionable intelligence from platform usage data to pinpoint a roadmap of optimizations designed to increase customer lifetime value (LTV) and system efficiency. What Success Looks Like Market‑Leading Data Strategy: A compelling, differentiated product vision that establishes our data platform as the "must‑have" solution for real‑time asset and facility intelligence. Engineering Grade Data Contracts: Seamless collaboration where data producers and consumers operate under robust data contracts, resulting in high data quality and decoupled, scalable architecture across our portfolio of products. High Velocity Stream Processing: An outcome driven roadmap that consistently delivers measurable ROI through optimized stream‑based processing and sub‑second latency for critical business insights. Standardized Data Modeling: A unified and intuitive semantic data model that reduces time‑to‑insight for internal teams and external customers alike. Platform Excellence: A culture of continuous discovery and experimentation that results in a frictionless, category‑leading user experience for data‑driven personas within our customer base. Quantifiable Growth Velocity: Sustained upward trends across core platform KPIs, specifically driving deeper adoption of real‑time data features, higher retention, and expansion revenue. Organizational Trust & Alignment: A unified cross‑functional engine where Data Engineering, Analytics, Design, and GTM teams operate with absolute clarity, shared technical standards, and a common purpose to deliver data enable user experiences across our entire product portfolio. What You Bring Data Platform Expertise: 8+ years of progressive Product Management experience, with a proven track record of scaling B2B SaaS data platforms and distributed systems. Technical Mastery: Deep understanding of data modeling (relational and dimensional) and the implementation of data contracts to ensure decoupled, high‑quality data exchange. Stream Processing Proficiency: Hands‑on experience defining requirements for stream‑based data processing (e.g., Kafka, Flink) and real‑time analytical workloads. Outcome Driven Leadership: A portfolio of successful product outcomes where you led the journey from an abstract data vision to a measurable market win. Discovery & Validation Rigor: Extensive experience in user centered discovery, partnering with UX and Engineering to move from ideation to validated, high‑conversion experiences via A/B testing and technical prototyping. Commercial & GTM Acumen: Proven success in defining positioning and launch strategies that drive real user adoption for complex technical capabilities. Analytical Fluency: Proficiency in leveraging complex datasets and system telemetry to diagnose platform health, identify growth levers, and make high‑stakes tradeoff decisions. Executive Presence: The ability to navigate organizational complexity and communicate technical concepts clearly to both engineers and C‑suite stakeholders. Educational Foundation: Bachelor’s degree in Computer Science, Data Science, or a related field required; MBA or advanced technical degree preferred. Preferred Qualifications Advanced Data Architecture: Deep familiarity with distributed systems, microservices architecture, and managing schema evolution at scale. Product‑Led Growth (PLG): Proven experience in PLG environments, specifically leveraging data transparency and self‑service analytics to drive user expansion. Modern Data Stack: Expert‑level use of cloud data warehouses (e.g., Snowflake, BigQuery) and advanced analytics platforms like Amplitude, Mixpanel, or Heap. Stream‑Processing Frameworks: Practical knowledge of real‑time data orchestration tools and stream‑processing engines such as Apache Kafka, Flink, or Spark Streaming. Enterprise Complexity: Background in managing complex workflow based products or large‑scale enterprise SaaS ecosystems. Advanced Degree: MS in Data Science, Computer Science, or an MBA with a focus on technical product management. Bonus or Equity This position is also eligible for bonus as part of the total compensation package. Pay Range The salary range for this position (in local currency) is 137,200.00 - 229,100.00 We are an Equal Opportunity Employer. Fortive Corporation and all Fortive Companies are proud to be equal opportunity employers. We value and encourage diversity and solicit applications from all qualified applicants without regard to race, color, national origin, religion, sex, age, marital status, disability, veteran status, sexual orientation, gender identity or expression or other characteristics protected by law. Fortive and all Fortive Companies are also committed to providing reasonable accommodations for applicants with disabilities. Individuals who need a reasonable accommodation because of a disability for any part of the employment application process, please contact us at View email address on click.appcast.io. #J-18808-Ljbffr Fortive Corporation (SE)