VP of Data Engineering

At MFour, we're transforming how businesses understand consumers in an increasingly complex, AI-driven world. Founded in 2011, we are a leading consumer intelligence platform delivering validated, connected, and opt-in data that powers smarter, faster decision-making.

What sets us apart is our ability to connect what consumers say with what they actually do. Through our proprietary platform, MFour Studio™ and our flagship app Surveys On The Go®, we combine survey data with real-world behaviors, creating a complete, accurate view of the consumer journey.

We're also shaping the future of research through innovations like DANI™ , our AI-powered assistant that enables teams to quickly analyze data, uncover insights, and take action with confidence.
Built on our Fair Trade Data® model, everything we do is grounded in transparency, privacy, and trust. Today, we partner with leading global brands like Google, Microsoft, and Disney to eliminate blind spots and drive better business decisions.

Your Journey to Success:

Our data is the product. Every Studio insight, every licensed data feed and every AI agent answer depends on pipelines that run on time and data that is provably correct. You will own that end to end.

You inherit a working platform - a verified mobile panel, behavioral app/web/location streams, a Databricks and Snowflake estate on AWS, and daily contractual feeds to data-licensing partners. Your job is to turn it into an operation that is measured, monitored, and on-call around the clock, and to build the team that runs it.

Your Mission:

Strategy and architecture

• Own the Data Platform roadmap, architecture and budget across ingestion, storage, transformation and delivery.
• Lead warehouse and lakehouse decisions (Snowflake, Databricks) with explicit cost, performance and lock-in trade-offs.
• Design identity resolution that links panelists to their devices, app, web and location signals without compromising privacy.

• Set SLAs for every production pipeline and hold the team to them.
• Build observability: data-quality tests, lineage, freshness and volume alerts, paging for failures at any hour.
• Stand up and staff a 24/7 on-call rotation for the Data Platform, integrated with incident management.
• Publish data-quality and panel-health metrics that leadership, Sales and clients can rely on.

• Deliver licensed data feeds (app, web, media, shopper, audio, social ad exposure, demographic) on contractual daily SLAs.
• Supply clean, modeled data to MFour Studio, crosstabs and our AI agents, including retrieval and evaluation datasets.
• Onboard new third-party data sources, including location data, and prove their match quality before release.

• Enforce hashed-PII handling, retention and consent rules in the pipelines themselves, not in policy documents alone.
• Partner with Security on access control, audit logging and compliance with CCPA/CPRA and other U.S. state privacy laws.

• Hire, coach, and retain data engineers; set the bar for code review, testing and documentation.
• Work daily with Product, Engineering, Customer Success and Data Licensing; translate data risk into business terms for the executive team.

What Sets You Apart

• 12+ years in data engineering, including 5+ years leading data engineering teams, with managers reporting to you.
• Hands-on depth in Python and SQL, and production experience with Snowflake and/or Databricks (Spark) on AWS.
• A record of running pipelines under external SLAs - data sold or delivered to customers, not only internal dashboards.
• Built data-quality and observability programs: automated tests, lineage, alerting, and on-call.
• Shipped identity resolution or entity matching across devices,…