Description:
We are seeking a hands-on Product Lead / Senior Product Manager with deep experience driving product discovery, owning product backlogs, leading sprint delivery, and shipping measurable outcomes in complex enterprise environments.
This role requires someone who can operate independently, move quickly, and manage multiple parallel workstreams across a federated or matrixed stakeholder environment. The ideal candidate brings strong product management depth in software, data, or platform products, with specific experience owning enterprise data governance, metadata management, data quality, or data lineage products.
This person should be highly skilled in design thinking and human-centered product methods, including user interviews, journey mapping, opportunity framing, and iterative validation. They should also be an active user of AI tools in their day-to-day product management workflow, using AI to improve discovery, analysis, documentation, prioritization, and delivery.
Key Responsibilities
• Lead product discovery efforts across multiple parallel workstreams, identifying real user needs, pain points, business opportunities, and measurable outcomes.
• Own and manage the product backlog, ensuring priorities are clearly defined, outcomes are understood, and delivery teams have the context needed to execute.
• Drive sprint planning, backlog refinement, user story development, acceptance criteria, and iterative delivery in partnership with engineering and design teams.
• Develop outcome-driven, incremental product roadmaps that balance business value, user needs, technical feasibility, and enterprise constraints.
• Apply design thinking and human-centered methods, including user interviews, journey mapping, problem framing, solution validation, and feedback loops.
• Partner with domain owners, data stewards, engineering leads, governance teams, and executive sponsors to align priorities and drive decisions.
• Lead or support product-driven buy-versus-build evaluations and vendor assessments for enterprise data tools.
• Own product work related to enterprise data governance, metadata management, data quality, data lineage, cataloging, or related data platform capabilities.
• Work independently in ambiguous environments, quickly ramping up on unfamiliar domains and translating complexity into clear product direction.
• Prepare high-quality executive-ready communications, recommendations, roadmaps, decision documents, and delivery updates.
• Actively leverage AI tools such as LLMs, Claude, GitHub Copilot, or similar platforms to improve product discovery, analysis, documentation, and workflow efficiency.
Required Qualifications
• 15+ years of product management experience in software, data, platform, or enterprise technology environments.
• Proven experience owning products end-to-end, including discovery, strategy, roadmap, backlog, delivery, launch, and outcome measurement.
• Demonstrated experience applying design thinking and human-centered methodologies, including user interviews, journey mapping, opportunity framing, prototyping, and iterative validation.
• Ability to cite specific projects, techniques, and outcomes where design thinking or human-centered product practices were applied.
• Proven ability to create and deliver outcome-driven, incremental roadmaps in complex enterprise environments with federated or matrixed stakeholders.
• Direct product ownership experience with at least one enterprise data governance, metadata management, data quality, data lineage, data catalog, or related data platform product.
• Hands-on product ownership experience with tools such as Collibra, Alation, Informatica, dbt, or comparable data governance, catalog, metadata, or lineage platforms.
• Strong understanding of enterprise data ecosystems, including data governance, stewardship, metadata, lineage, quality, controls, and stakeholder workflows.
• Strong facilitation and influence skills, with the ability to align domain owners, data stewards, engineering leads, business stakeholders, and executive sponsors without formal authority.
• Demonstrated use of AI tools such as LLMs, Claude, GitHub Copilot, or equivalent tools as part of day-to-day product management work.
• Strong executive communication skills, including the ability to synthesize complex topics, manage ambiguity, and produce clear, high-quality deliverables.
• Experience leading product-driven buy-versus-build evaluations and vendor assessments for enterprise data tools.
Nice-to-have
Experience in financial services or a regulated industry — familiarity with data privacy, compliance, audit trail requirements, or data retention policies
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