Sr Product Manager (Data)

Arionkoder; United States; Remote; USD 140,000 - 190,000; Full time

Benefits offered by this job

Monthly USD Service Fee

Paid Time Off

Caregiver Time Off

Remote work from anywhere

Entrepreneurial environment

Job summary

Arionkoder is seeking a Senior Product Manager to lead the Enterprise Context Layer for a US-based client. You will decide what gets built, align business units on data definitions, and challenge architects to deliver value.

You will run discovery with stakeholders, define owned metrics, drive adoption, and ensure the shared data layer is used across teams. You will partner with Solution Architects and PM to sequence work and deliver AI-enabled capabilities.

Qualifications

• 5+ years in product management with data products experience.
• Experience aligning stakeholders 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.
• 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 (Databricks, Snowflake, dbt, data catalogs or governance tooling).

Responsibilities

• 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.

Skills

Data products

Stakeholder alignment

Discovery & prioritization

AI/LLM products

English fluency

Tools

Databricks

Snowflake

dbt

Data catalogs

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.

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).

• 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.