Technical Product Manager, iSpot.tv

• 4+ years of product management experience, ideally in data infrastructure, ad-tech, or mar-tech
• Bachelor’s degree in related field

Desirable

• At iSpot.tv, you’ll join a dynamic and innovative team committed to revolutionizing the television and video advertising landscape. Our cutting-edge technology and data analytics powers decision-making across the advertising and media ecosystem
• As a Technical Product Manager, Integrations and Identity, you’ll drive the evolution of our data integrations and identity infrastructure
• This role sits at the intersection of product, engineering, and data science—responsible for defining the pipelines and APIs that ingest, map, and unify vast datasets for our clients and partners
• You'll play a critical role in defining and delivering data products that power our core features across our measurement and attribution platforms
• If you’re passionate about building scalable data products, live for creating elegant design from messy datasets, and get excited about technical problem solving, you’ll thrive here
• Drive the roadmap for our data onboarding and identity resolution capabilities. Define and prioritize how external datasets are ingested, matched, and unified across platforms. Balance infrastructure scalability, partner needs, and long-term identity resolution goals. Collaborate cross-functionally to align roadmap milestones with company OKRs and data strategy
• Own API and data integration workflows. Manage the design and implementation of APIs and ETL workflows that ingest and normalize data from partners, publishers, and clients. Work hands-on with engineering to ensure technical feasibility and scalability, and partner with data science to align on requirements to support matching logic, data enrichment, and modelling strategies
• Collaborate with data partners and clients. Act as a technical liaison during integrations—working directly with partners to map their data fields, understand row level nuances, resolve schema mismatches, and navigate privacy or contractual limitations. Document and standardize onboarding playbooks to streamline future integrations
• Drive development of privacy-safe identify matching, inclubing both deterministic and probabilistic methodologies. Partner with data science to evaluate and iterate on deterministic keys (e.g., hashed emails, device IDs) and probabilistic techniques, ensuring explainability and measurement integrity
• Ensure alignment with privacy, compliance, and data governance best practices. Work closely with legal, compliance, and security teams to ensure all identity-related data flows are compliant with regional and global privacy frameworks (e.g., CCPA, GDPR)
• Translate complex technical requirements into clear product specs and user stories. Break down technical concepts like match confidence thresholds, schema evolution, or differential privacy techniques into actionable requirements for engineering. Write user stories and acceptance criteria that are traceable to broader business outcomes and easy for non-technical stakeholders to understand
• Establish and track KPIs for data integration health, coverage, and performance. Define operational metrics to monitor the reliability, completeness, and freshness of ingested datasets (e.g., match rates, latency, ID coverage, null field %). Build dashboards and partner with analytics to ensure visibility into data pipeline quality and partner SLA adherence