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Salary: USD 205,200 - 295,000 / annual
Apollo.io is a leading go-to-market platform trusted by over 500,000 companies globally, providing sales and marketing teams with verified contact data for 210+ million B2B contacts and 35 million companies, plus engagement and conversion tools in one unified platform. Founded in 2015, valued at $1.6 billion, and backed by Sequoia Capital and Bain Capital Ventures, Apollo is expanding from prospect discovery and outreach to comprehensive GTM motion support.
This Principal Product Manager role owns Apollo Data—the foundational data layer providing the world's most accurate B2B company, contact, and signal data. You will drive the product vision, strategy, roadmap, and delivery for Apollo's core data catalog, ensuring it remains the backbone enabling the agent, API, and workflow surfaces that power GTM at scale.
Key responsibilities include:
- Owning product vision, strategy, roadmap, and delivery for the core data catalog
- Managing Apollo's central data telemetry: metrics and dashboards defining catalog breadth, depth, accuracy, and freshness
- Leading the always-on data sourcing operation, including source identification, evaluation, and integration
- Bridging R&D and Partnerships on vendor data sourcing and relationships
- Collaborating with Engineering on data catalog innovations with a product and GTM lens
- Supporting key customer data initiatives with direct customer interaction alongside sales and field teams
- Driving cross-functional alignment across Product, Engineering, Design, GTM, Support, and Enablement
- Getting close to customers and GTM teams to identify data gaps and accuracy issues
- Setting product strategy for data presentation across the product: enrichment, search, filters, scoring, taxonomy, and data structure
- Prototyping quickly using AI-native tools (Claude Code, Cursor, Lovable, Figma AI) to validate ideas before scaling
- Turning complex data pipelines into simple, trustworthy customer experiences
- Leading build vs. buy vs. partner decisions for data sources, evaluating on coverage, accuracy, freshness, cost, and compliance
- Defining KPI trees and learning loops to prioritize, measure, and iterate
- Writing crisp strategy docs, PRDs, launch plans, and tradeoff memos
Requirements:
- 7+ years of product management experience, including ownership of complex data-centric product areas from strategy through launch
- AI-native builder: proficiency with Claude Code, Cursor, Lovable, Figma AI, or similar tools; ability to point to things you built or shipped, not just specs written
- Principal-level ownership across a meaningful product area with company-level visibility
- Strong product judgment: ability to identify highest-leverage problems, make hard tradeoffs, and protect focus
- Data thinker: ability to navigate complexity of multiple data sources and aggregation processes; design and leverage data-backed telemetry for product decisions
- Compliance fluency: understanding of data privacy, GDPR, CCPA, consent, and licensing constraints; ability to design within them and partner with Legal and Privacy
- High agency: ability to create clarity in ambiguous environments and move work forward without waiting for perfect structure
- Technical fluency across architecture, reliability, observability, APIs, data models, instrumentation, and edge cases
- Customer empathy for how data gaps, stale records, and inaccuracies erode trust for sales, marketing, RevOps, admins, and end users
- Execution excellence: ability to define, ship, measure, and iterate without thrash
- Strong influence and communication: ability to align teams, build trust quickly, and make complex systems feel simple
Nice to have:
- Experience with B2B data products, data marketplaces, enrichment, identity resolution, or data-as-a-service businesses
- Familiarity with entity resolution, record matching, data freshness and decay, confidence scoring, high-scale data collection and verification
- Experience sourcing, evaluating, and negotiating third-party data vendor relationships, including waterfall or multi-vendor architectures
- Experience building for sales, marketing, RevOps, customer success, or GTM operators
- Experience using analytics, experimentation, observability, or support data to improve data quality and customer outcomes
