DoubleVerify - Senior Manager, Software Engineering - Data Platform & AI Enablement
Requirements
• Experience managing engineering teams responsible for data platforms, pipelines, APIs, or infrastructure. • Strong technical judgment across data architecture, data reliability, and application-facing access patterns. • Proven ability to lead cross-functional initiatives across Engineering, Product, Data Science, and Customer Success. • Track record of delivering platform improvements with measurable business impact. • Ability to operate at broader organizational scope beyond a single functional team. • Strong people leadership, communication, and execution skills. • Experience with datalake or warehouse adoption across multiple teams. • Experience building Data APIs, permissions systems, or customer-facing data access layers. • Experience with AI-enabled workflows, LLM tooling, or agentic data access patterns. • Experience reducing operational load through automation. • Familiarity with marketing analytics, MTA, MMM, testing, and customer data platforms. • Success Measures • Clear ownership across Data, APIs, permissions, and customer-facing access. • Reliable and timely client data delivery. • Faster execution on AI-enabling Data API initiatives. • Broader datalake adoption across internal teams. • Reduced dependency bottlenecks between Data and Applications. • Improved engineering capacity through automation. • Strong retention and development of critical engineering talent.
Responsibilities
• Lead engineering teams responsible for data ingress, pipelines, datalake adoption, Data APIs, permissions, and data access interfaces. • Own execution and technical direction across Rockerbox’s data foundation and customer-facing data access layers. • Ensure reliable, timely, and scalable client data delivery. • Align ingestion, aggregation, API access, permissions, and AI-enabled data workflows under clear ownership. • Partner with Product, Applications, Integrations, Data Science, Customer Success, and DV stakeholders on platform strategy. • Enable internal teams and customers to access Rockerbox data through APIs, CLI tooling, and future agentic workflows. • Improve team efficiency through automation, reduced maintenance burden, and clearer ownership. • Manage, develop, and retain engineers through a period of organizational transition. • Reduce bottlenecks between Data, Applications, and customer-facing product development.
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