Technical Data Product Manager

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October 15

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Forbes

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Media • Finance • B2C

Forbes is a prominent global media company, known for its brand of content covering a wide range of topics such as business, investing, technology, entrepreneurship, leadership, and lifestyle. It features news, analysis, and information about issues of concern to industry leaders and affluent individuals. Forbes is widely recognized for its authoritative rankings of businesses and industry leaders, such as the Forbes Global 2000, and is a trusted source for in-depth analysis of current events and trends in the financial and corporate worlds. Through its digital and print platforms, Forbes engages its audience with high-quality journalism and thought leadership content.

201 - 500 employees

Founded 1917

📱 Media

💸 Finance

👥 B2C

💰 $200M Corporate Round on 2022-02

📋 Description

• Own the Product Vision · Define and evolve the strategy for our revenue attribution pipeline, balancing current needs with future scalability. • Maintain a clear roadmap of enhancements, technical upgrades, and new use cases aligned with business goals. • Drive clarity around what good attribution looks like — and where it can power better decision-making. • Collect and synthesize requirements from RevOps, Paid Media, and GM teams into actionable product specs. • Write clear logic, schema documentation, and join requirements for data engineers to implement. • Own the accuracy, usability, and interpretability of attribution outputs across stakeholders. • Coordinate delivery across Engineering, Data Ops, and RevOps in a matrixed environment. • Track implementation progress, flag blockers, and ensure delivery aligns with sprint timelines. • Communicate proactively with business stakeholders about what’s changing, why, and what they’ll get. • Work with business users to embed attribution into decision workflows — from bidding strategies to partner payouts. • Provide context, documentation, and structured demos to increase usage and trust. • Identify where adoption gaps exist and iterate to close them. • Partner with leadership to define next-gen use cases — from cross-channel attribution to modelled revenue to audience insights. • Contribute to long-term visioning around how attribution evolves in a privacy-constrained, ML-augmented world. • Explore how new data, platforms, or frameworks could expand our impact.

🎯 Requirements

• Experience working on attribution, revenue modelling, or marketing performance data products. • Strong fluency in SQL, data modelling, and business logic — you can write detailed specs for engineers – but practical implementation not required. • Excellent communication skills and stakeholder management instincts. • Experience operating in matrixed or cross-functional environments. • Ability to balance short-term delivery with long-term product thinking. • Experience with GCP (BigQuery, Cloud Composer, Cloud Functions in particular) (Nice to Have). • Familiarity with marketing data, paid media (Google Ads, Meta), and RevOps workflows (Nice to Have). • Exposure to ML use cases (e.g. modelled revenue, LTV and attribution) (Nice to Have). • Comfort building diagrams, brief documents, and supporting light QA or UAT when needed (Nice to Have).

🏖️ Benefits

• Work on one of the most business-critical data products in the company. • Collaborate with top-tier talent across data, marketing, and product. • Remote-first culture with flexibility and trust. • Influence both what we build and how we work — shaping attribution for the future. • Be part of a mission-driven team that blends journalism, technology, and strategy.