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Product Manager, Data Lake

Wise

About this role

Job title: Product Manager, Data Lake

About the Role Wise is building a new data lake to underpin analytics, reporting and AI. You will own this platform as a product, leading the move from legacy systems to a modern lakehouse, from roadmap to adoption. You’ll work with a dedicated engineering team and be guided by the Product Lead for Data Products & Insights, but own the roadmap.

What You'll Do

  • Own one of Wise's biggest product bets: the data lake at the core of data infrastructure, supporting real-time fraud detection, workforce management, analytics, financial reporting, and big data use cases yet to be built.
  • Treat the teams who run on that data as customers: understand their needs, decide what the platform should excel at, and shape the roadmap around the value each step creates.
  • Drive adoption one workload at a time: ensure every dataset moved is faster, cheaper, or more trustworthy.
  • Onboard teams onto the platform, observe where they struggle, and translate that into product improvements.
  • Define and track the measures that matter: adoption, query performance and cost, data quality incidents, and trust in data.
  • Build metadata, ownership and access controls in from the start to grow trust as usage expands.

What We're Looking For

  • Around 3 to 5 years of product experience, or mix of product and hands-on data work, with at least two platform products shipped end to end.
  • Background in data infrastructure: pipelines, warehouses or lakes; comfortable with SQL.
  • Ability to turn ambiguous technical work into a clear, staged roadmap with measurable outcomes.
  • Experience working closely with engineers, and the communication skills to explain technical trade-offs to non-technical colleagues.
  • Care for the people who use data: talking to users, observing where they struggle, and turning that into product improvements.

Nice to Have

  • Hands-on experience with the modern data stack (Iceberg or Delta, Snowflake or Databricks, dbt or Airflow).
  • Experience with data migration or re-platforming projects (product or engineering side).
  • Experience in financial services or another regulated industry.

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