СШАManager, Product Management
4 нед. назад
145k–230k USD / годСШАMiddle
Product Manager role at , focusing on their cloud-native SaaS platform for enterprise data management.
Обязанности
- is looking for a Manager, MDM Operations & Product Management to join our Product Management organization. This is a high-impact, player-coach role that operates across two complementary tracks: product delivery and MDM operations .
- On the product side, you will own and drive a roadmap of platform capabilities — delivered through the core platform and IDE — that directly reduce time-to-value for implementations. You'll work closely with Engineering and Product leadership to define, prioritize, and ship features that make implementations faster, more repeatable, and less dependent on manual effort.
- On the operational side, you'll own and advance 's own internal instance of the platform — our " on " deployment. This means continuously improving our internal data unification capabilities, expanding master data coverage across the organization, and enabling agentic access to master data so that internal teams can act on trusted, unified data with minimal friction. You'll lead a small team of analysts and implementation specialists who operate, extend, and evolve this environment as a strategic internal asset.
- This is a role for someone who can think like a product manager, execute like a practitioner, and lead a team with clarity and purpose.
- By the end of your first year, you will have:
- Delivered platform and IDE capabilities — shipped and adopted — that measurably reduce implementation cycle time
- Published an actively-used library of implementation accelerators consumed by PS and partner teams
- Materially improved the quality, coverage, and utility of 's internal master data environment
- Enabled at least one meaningful agentic use case powered by unified internal master data
- Established your team as the authoritative owner of both 's internal MDM operations and its TTV product investments
Будет плюсом
- Experience in MDM platforms beyond (Informatica, Tibco, Profisee, etc.)
- Familiarity with healthcare, life sciences, or B2B customer data use cases
- Experience measuring and reporting on data quality KPIs, implementation metrics, or product adoption metrics
Условия
- At , we carefully consider a wide range of compensation factors to determine your personal top of market. We rely on market indicators to determine compensation and your specific job family, background, skills, and experience to get it right. These considerations can cause your compensation to vary and will also be dependent on your location.
- Overall Market Range
- $145,000 — $230,000 USD
Другое
- At ®, an SAP Company, we believe data should fuel your success in the enterprise AI era. Our Context Intelligence Platform turns fragmented data into a trusted, connected context so AI agents and systems can act with expert-level judgement at enterprise scale. ’s cloud-native SaaS platform harmonizes, unifies, and governs data across sources and formats—including unstructured data—in real time, turning them into data assets that can be mobilized in milliseconds to any application, user, or AI agent. Trusted by more than 200 of the world’s largest brands across industries such as life sciences, financial services, healthcare, and technology, we fuel frictionless operations and help enterprises accelerate innovation and reduce risk.
- At , our values guide everything we do. With an unyielding commitment to prioritizing our “Customer First”, we strive to ensure their success. We embrace our differences and are “Better Together” as One . We are always looking to “Simplify and Share” our knowledge when we collaborate to remove obstacles for each other. We hold ourselves accountable for our actions and outcomes and strive for excellence. We “Own It”. Every day, we innovate and evolve, so that today is “Always Better Than Yesterday”. If you share and embody these values, we invite you to join our team at and contribute to our mission of excellence.
- has earned numerous awards and industry and analyst recognition for our technology, our culture, and our people. was founded on a distributed workforce and offers flexible work arrangements to help our people manage their personal and professional lives. If you’re ready to work on unrivaled technology where your desire to be part of a collaborative team is met with a laser-focused mission to enable digital transformation with connected data, let’s talk!
- Own a product roadmap focused on TTV improvement, spanning features in the core platform and IDE that reduce implementation complexity, accelerate configuration, and lower the barrier to productive deployments
- Translate implementation friction — sourced from PS delivery, partner feedback, and customer data — into clearly scoped product requirements and user stories
- Partner with Engineering to prioritize and deliver capabilities that have measurable impact on implementation cycle time: guided configuration workflows, IDE productivity enhancements, validation tooling, template-driven setup, and similar
- Build and maintain a curated library of implementation accelerators — configuration templates, data model patterns, integration scaffolding, and validation tooling — grounded in real-world deployments and informed by the internal instance
- Define success metrics for shipped capabilities and track adoption and impact post-launch; establish clear cycle time benchmarks and report on measurable TTV reductions over time
- Represent the implementation practitioner perspective in product planning and roadmap reviews, ensuring that time-to-value remains a first-class product concern
- Own and operate 's internal deployment as a living, production-grade MDM environment — not a demo instance, but a strategic platform for internal data unification
- Continuously improve data unification quality across internal domains: expanding entity coverage, refining match and survivorship rules, and closing gaps in master data completeness and accuracy
- Drive the expansion of agentic access to master data — enabling AI agents and internal tools across the organization to query, consume, and act on unified master data through well-defined interfaces
- Define and enforce data governance standards for the internal instance, ensuring master data remains authoritative, consistent, and trustworthy as coverage grows
- Surface learnings from internal operations back into the product roadmap — the internal deployment is both a customer zero environment and a proving ground for new platform capabilities
- Lead a team of 2–4 operations analysts and implementation specialists, providing direction, mentorship, and prioritization support across both the internal MDM operations and product workstreams
- Balance your own hands-on contributions — configuring entities, authoring product requirements, designing tooling — with the coaching and coordination your team needs to operate effectively
- Partner with Product Management leadership to ensure investments across product delivery and internal operations are aligned and mutually reinforcing
- Work closely with Engineering, Product, IT, and business stakeholders to expand master data utility across the organization
- Serve as the connective tissue between internal data consumers, agentic tooling teams, and the platform roadmap
- Represent internal operational experience in product planning discussions, ensuring the platform serves real-world operational needs
- Hands-on experience with the platform — including entity configuration, matching and survivorship rules, data pipelines, IDE, and API behavior; you've delivered or overseen real implementations
- Product management experience — you've owned a roadmap, written requirements, worked with engineering teams to deliver software, and measured outcomes post-launch; you know how to move something from problem to shipped capability
- Background in SaaS implementation or professional services , with a track record of delivering complex data or MDM solutions in customer-facing or internal delivery roles
- Experience operating or administering a production MDM environment, including ongoing data quality management and governance
- Strong technical fluency — comfortable reading and writing configuration JSON, scripting, evaluating API behavior, and working directly in IDE; can prototype and validate tooling yourself when needed
- Familiarity with agentic AI patterns and how AI agents consume structured master data via APIs or MCP-style interfaces is a meaningful plus
- Demonstrated ability to lead small teams, including setting direction, managing priorities, and developing talent
- Excellent written communication; capable of producing PRDs, runbooks, documentation, and asset deliverables that engineering teams and practitioners can act on without hand-holding
- Comfortable operating with ambiguity and building structure where none yet exists