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Sr Product Manager (Data)

Arionkoder

Senior Product Manager for a data-focused enterprise context layer. You will lead the strategy and execution of shared data definitions and governance to power AI agents and internal automations.

What you’d own

  • Enterprise Context Layer (shared definitions, entities, and access rules)
  • Discovery sessions with business and technical stakeholders
  • Cross-team alignment on metrics and data ownership
  • Hypothesis-driven discovery and prioritization processes

Who it’s for

A fit if you…

  • ✓5+ years of experience in product management specifically for data products
  • ✓Proven ability to align disparate business units on shared definitions
  • ✓Experience delivering AI or LLM-based products
  • ✓Technical depth to challenge architects on modeling and trade-offs

Not for you if…

  • ✗You prefer building standalone features over organizational data governance
  • ✗You prefer clear, pre-defined requirements over discovery-heavy roles
  • ✗You prefer a pure engineering environment without heavy stakeholder management

Reading between the lines

  • The focus on 'getting products adopted' and 'securing sponsorship' suggests significant internal politics and change management work.
  • The requirement to 'challenge architects' and 'push back' implies a high-autonomy role where you must defend product decisions against technical constraints.

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Benefits

PTOParental Leave
Full job description

Arionkoder is an AI consulting firm helping companies build, embed, and own AI systems that drive real business outcomes. We combine Product Development, Artificial Intelligence, and Team Augmentation to craft digital products and solutions that create lasting impact — guided by a human-centric approach and a commitment to pushing the boundaries of what technology can do. We are looking for a Senior Product Manager to lead the product side of an Enterprise Context Layer for a US based company: the shared layer of agreed definitions, resolved entities, governed knowledge and access rules that their AI agents, customer-facing products and finance automations will draw on.

You will decide what gets built and why, get business units to agree on what their data means, and challenge the architects and engineers who build it while driving internal adoption What you'll do Lead discovery with business and technical stakeholders: run working sessions, surface how data is used today, and turn what you learn into a prioritized set of use cases and requirements. Own definitions and ownership: identify where metrics and business terms are inconsistent across teams and systems, and drive them to agreed, documented definitions with a named accountable owner for each.

Lead adoption across the business: get the teams that publish data to own its definitions, metrics and quality, and get the teams that consume context to draw from the shared layer rather than building their own version. Secure sponsorship and alignment at the leadership level when teams disagree. Run a hypothesis-driven process: capture the client's assumptions, assign each to the session or experiment that validates it, and close each with a clear verdict and rationale.

Shape each increment with the Solution Architect: define scope, acceptance criteria and the order of vertical slices based on business value and risk. Challenge technical decisions from a business perspective: ask whether a data model, a definition or a trade-off serves the people who will depend on it, and push back when it does not. Keep a clear cadence with the Project Manager: decisions, open questions, risks and stakeholder commitments are tracked and visible.

Transfer ownership: leave the client with the processes, documentation and ownership model to keep the layer accurate after we step back. What we're looking for (required) 5+ years in product management, with experience on data products (analytics, data platforms, metrics or semantic layers, internal data tools or similar). Experience aligning stakeholders across business areas on shared definitions, priorities and ways of working. A structured, evidence-based approach to discovery and prioritization.

Comfortable making decisions with incomplete information and managing senior stakeholders. A record of getting products adopted, not just delivered. Experience in defining, designing and delivering AI or LLM-based products. Fluent written and spoken English. Strong plus Enough technical depth to challenge data architects and engineers on technical definitions, modeling choices and trade-offs, and to understand their answers. Familiarity with modern data stacks (for example Databricks, Snowflake, dbt, data catalogs or governance tooling).

Perks 💵 Monthly USD Service Fee 🌴 20 business days of paid Agreed Time Off—Annual + 6 Local Holidays 🐣Caregiver Time Off 💻 A dynamic remote work culture. You can work from anywhere! 🚀An entrepreneurial environment. About us In 2010, our founders dreamed up a company that could positively impact the world. Since then, we've been in permanent evolution: from business consulting to innovation and design, and now to building amazing digital products powered by AI.

We scaled globally, launched AI Labs and Reshape Studios, and claimed our space as an AI consulting firm — helping organizations move from pilots to production through accountable AI. Today, we're expanding our impact across industries, driving real AI adoption through accountability, governance, and value at scale. Dreamers first, builders always.

About Arionkoder

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Arionkoder is an AI consulting firm that helps companies plan, build and govern AI systems they own, from strategy and readiness assessments to applied solutions and embedded engineering, product and design teams. Clients span pharma, oil and gas, logistics and health tech, with case results like 95-100% search accuracy from hybrid AI agents. Founded in 2020 and now around 200 people, it has moved from software and team augmentation into AI consulting. It runs on its own delivery frameworks (The Foundry, Delivery OS, T.R.U.S.S. for AI governance), which makes it a distinctive place for PMs who like consulting-style, outcome-driven work.

AI & Machine LearningEnterprise Software

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