Product Manager - Data & Insights

Role overview

Key responsibilities

• Define roadmaps for customer analytics, reporting portals, and internal reporting infrastructure; align priorities with business goals and customer needs.
• Gather cross-functional requirements and translate business questions into feature requirements, user stories, acceptance criteria, data contracts, and KPIs.
• Partner on warehouse data models and marts; influence ETL/ELT, dimensional modeling, and architecture decisions.
• Own data definitions, taxonomy, lineage, version control, and processes for quality verification and anomaly detection.
• Own reporting and BI product experiences; improve self-service analytics and dashboard usability through user feedback.
• Present updates and insights, bridge technical and business teams, and facilitate decisions about data accuracy, availability, and reporting timelines.
• Champion data compliance across products and promote responsible, secure data management.

Experience and qualifications

• 5+ years of experience in product management, data, analytics, or reporting platforms, with a focus on data-driven products.
• Proven delivery of customer-facing reporting products, dashboards, and internal analytics solutions.
• Experience working with data engineers, analysts, product teams, UX, and business stakeholders.
• Strong SQL and data modeling knowledge, including fact and dimension tables and star schemas.
• Hands-on experience with data warehouses such as ClickHouse, Vertica, or Snowflake and BI tools such as Metabase, Tableau, Looker, Power BI, or Sigma.
• Strong understanding of data privacy, governance, compliance, quality, integrity, scalability, and performance; GDPR and PDPL are named frameworks.
• Ability to define KPIs and turn business and reporting needs into clear data and product requirements.
• Bachelor’s degree in Computer Science, Data Science, Business, Engineering, or a related field.
• Familiarity with ELT pipelines, dbt, and data orchestration is a plus.

AI proficiency and toolkit

• AI proficiency at minimum Level L4 for product discovery, specification, prototyping, and stakeholder communication.
• Hands-on experience with Claude and Lovable; use structured prompts and refine prompts rather than manually patching outputs.
• Use AI to synthesize interviews, tickets, and reviews into themes, validating insights against source data.
• Draft PRDs, user stories, and executive updates with AI, then verify claims and numbers before sharing.
• Build clickable Lovable prototypes for stakeholder validation; distinguish prototypes from production-ready products.
• Understand AI agents, including prompts, tools, memory, and guardrails; identify workflows suitable for automation.
• Recognize AI risks including hallucination, bias, data privacy, and over-reliance.
• Toolkit includes data warehouses, BI/reporting tools, SQL, data modeling, data marts, pipelines, ETL/ELT, dbt, orchestration, governance, quality, lineage, and compliance.

Working style

Benefits

• Competitive salary and bonus, share scheme, 30 holiday days after the first anniversary, and a birthday day off.
• Option to work from anywhere in the world for up to 25 days per year.
• Paid leave for new parents.