Verve

Technology

DataEngineeringManager

₹30–50L ~AI est. Bangalore, India FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Manager candidates.

The Brief

“Data Engineering Manager at Verve”

Industry & Context.

Technology
Full Job Description

Who We Are Verve has created a more efficient and privacy-focused way to buy and monetize advertising. Verve is an ecosystem of demand and supply technologies fusing data, media, and technology together to deliver results and growth to both advertisers and publishers–no matter the screen or location, no matter who, what, or where a customer is. With 30 offices across the globe and with an eye on servicing forward-thinking advertising customers, Verve’s solutions are trusted by more than 90 of the United States’ top 100 advertisers, 4,000 publishers globally, and the world’s top demand-side platforms. Learn more at verve.com. What You Will Do Provide full supervision and support for the local data engineering pod, spanning both data-platform and analytics/reporting work streams. Manage team capacity, lead hiring to backfill and grow the pod, and define team charters that support a fast-evolving data platform roadmap. Foster a high-performance culture across a distributed organization (Bangalore and EU), onboarding recent hires and establishing strong operational discipline (on-call/IRM, runbooks, incident response). Plan and execute multi-quarter initiatives with many interdependencies (e.g., the data lakehouse re-architecture (Apache Flink on GKE), the dedicated CTV late-impression pipeline, and CI/CD automation (ArgoCD)) ensuring alignment with architectural standards. Refine the team's engineering processes, methodologies, and technical standards: code quality, infrastructure-as-code, deployment automation, observability, and cost optimization. Partner closely with Product Management, Backend Engineering, Data Science, and Analytics to align the platform roadmap with business objectives. Stay active in technical implementation (estimated 50-70% hands-on): designing pipelines, delivering new product features, reviewing architecture and code, addressing tech debts, and troubleshooting production data issues. Undertake production responsibilities including setting up

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