VP, Data Experience

dentsu•New York, NY

1d•$136,000 - $240,000•Hybrid

About The Position

The purpose of this role is to set the strategic direction for the team, taking ownership of the overall vision and outcomes, liaising with other channels to ensure an integrated approach/roadmap. You will own data solutions and dashboarding end to end — the data engineering underneath them, the load-and-transform (LT) pipelines that feed them, and the Databricks lakehouse they run on — delivered through Dentsu Connect using our proprietary technologies, including Data Refinery and Taxonomy Monitor & Manager. This is media-fluent, client-facing leadership: you know how media works, how channel data connects, and how to make it trusted. Product-minded, automation-forward, and AI-obsessive is the operating posture — you ship data products, not one-off reports.

Requirements

10+ years across analytics, data engineering, and media data with progressive leadership responsibility
Deep media fluency — how media is planned, bought, and measured, and how ad server, DSP, search, social, and site-served channel data fit together
Hands-on experience performing crosswalks between media platforms — de-duplicating and connecting data between an ad server and a DSP, and reconciling delivery across sources
Thorough understanding of reach and frequency data — the complexity of attribution windows, and how unique reach is measured and de-duplicated across channels and partners
Thorough understanding of site-served digital partners and the realities of working with their data
Strong Databricks and Spark experience — lakehouse architecture, pipeline development, and data modeling for analytics
Enterprise dashboarding experience (Power BI preferred) — semantic models, governed datasets, and template-driven build
Track record building and leading data teams, including client-facing delivery at senior client altitude
A product mindset — roadmaps, iteration, and shipping durable data products rather than deliverables that die in an inbox

Nice To Haves

Experience with CPG or FMCG clients or brands
Experience in media agency or advertising technology environments
Experience with data sourcing, standardization and taxonomy governance tooling
Demonstrated AI adoption — LLM-assisted workflows, agentic automation, or AI-powered analytics in real production use
Experience managing offshore engineering teams
Knowledge of media data sources (CM360, SA360, Amazon Ads, Meta, TTD, programmatic exchanges)

Responsibilities

Own the end-to-end data experience — data solutions, dashboarding, and the data engineering behind them — as the single-threaded data leader on a dedicated client team
Design and run load-and-transform (LT) pipelines on Databricks that land media data into a normalized, analysis-ready structure — retiring manual pulls and one-off feeds as you go
Lead the dashboard build — scope, engineer, and ship Power BI dashboards on governed data products using DEx templates, engineered for reuse rather than one-off reporting
Deliver through Dentsu Connect — putting dentsu's proprietary technologies to work, including Data Refinery for standardized data ingestion and Taxonomy Monitor & Manager for naming governance
Own cross-channel data connection — design the crosswalks that de-dupe and join media data across platforms, reconciling ad server delivery with DSP activity into a single trusted view
Manage site-served and digital direct partner data — establish ingestion, mapping, and QA for partner-supplied data where standard ad-server tracking doesn't reach
Translate media into data models — partner with planning, investment, and analytics teams so the data foundation supports pacing, performance, and effectiveness use cases
Automate relentlessly — replace recurring manual work with pipelines, orchestration, monitoring, and alerting; treat any repeated manual step as a defect to engineer away
Push AI into the product — apply LLM and agentic capabilities to data QA, taxonomy compliance, insight generation, and the dashboard experience itself
Recruit, develop, and lead the team — onshore and offshore engineers and BI developers; set standards, review the work, and grow the talent