Director of Data Engineering

Vibe

1d • Hybrid

About The Position

You'll join the Engineering org as the chief architect of Vibe's entire data ecosystem — owning the infrastructure that ingests terabytes of data daily, governs it, and serves it to our Analytics, ML, and Product teams.

This role exists because Vibe is making the leap from startup speed to enterprise trust. We're building Nebula — our proprietary identity graph and data interoperability layer — and standing up the ML platform that powers real-time bidding at scale. We need someone who can architect both, and bring the team along for the ride.

Three reasons a great candidate should care:

You'll architect something rare. Nebula is a genuinely hard problem — identity resolution, data clean rooms, privacy-safe partner data exchange. You won't find work like this everywhere.
The timing is right. We're at the inflection point between scrappy and scalable. You'll shape how a category-defining company builds its data foundation — before the patterns are set.
You'll have real ownership. P&L responsibility, architectural authority, and a direct line to the CTO and VP Product. Your decisions will ship.

Requirements

• Hands-on experience architecting large-scale data platforms — you've designed systems ingesting TBs of data, not just managed teams that did
• Deep knowledge of data governance and compliance frameworks — CCPA, GDPR, SOC2 — and a track record of implementing them without killing engineering velocity
• Experience with identity resolution, device graphs, or privacy-safe data matching (clean rooms, entity resolution)
• Strong understanding of the ML lifecycle: data prep, training, deployment, monitoring — and the infrastructure that makes it work at scale
• Experience owning cloud infrastructure costs and optimising unit economics across AWS or GCP
• Prior experience in a regulated data environment — you understand publisher contracts, DPAs, and what data you can and cannot use

Nice To Haves

• Hands-on experience with clean room technologies (Snowflake Data Clean Rooms, AWS Clean Rooms, LiveRamp Safe Haven, or similar)
• Familiarity with MLOps tooling — feature stores (Feast, Tecton), model serving (SageMaker, Ray Serve), orchestration (Airflow, Dagster)
• Background in streaming TV, connected TV, or programmatic advertising infrastructure
• Experience leading a technical team through a SOC2 certification process

Responsibilities

• Architect the data platform
• Own the technical design of Nebula — Vibe's identity graph, entity resolution pipelines, and data clean room integrations with partners including major broadcasters
• Define the end-to-end data architecture serving Analytics, ML, and real-time bidding systems
• Solve training vs. inference skew: ensure data used to train models matches data available at bid time
• Build the ML infrastructure
• Design and ship the ML platform — feature stores, model registries, and CI/CD for ML — so data scientists can deploy models to production without infrastructure blockers
• Own the "golden path": a data scientist pushes code, a model retrains and deploys automatically
• Bridge the gap between Data Engineering and Data Science; remove friction, not just document it
• Lead governance without slowing people down
• Champion the transition to a security-first culture — SOC2, RBAC, PII anonymization — without turning compliance into a bottleneck
• Build guardrails, not gatekeepers: automated policy checks that let engineers ship fast and safely
• Own data retention policies, access controls, and governance frameworks across 200+ data assets
• Own infrastructure economics
• Hold the Data Platform P&L — track unit economics, separate storage costs from ML training costs, and ensure spend scales with revenue rather than ahead of it
• Optimise across a hybrid stack: high-volume streaming (Kafka/Kinesis), log storage (S3/Athena), and GPU compute for ML training
• Identify waste fast; distinguish inefficiency from intentional growth investment
• Lead the team
• Manage and grow the Data Platform Engineering team
• Assess current team capabilities against what's needed to ship Nebula and the ML platform
• Build a culture where engineers adopt structure because it makes them faster, not because they're told to

Benefits

• Equity — Employee Stock Ownership Plan. You're building this; you should own part of it.
• Variable pay — based on objectives you hit. No arbitrary targets.
• Hybrid flexibility — We're in the heart of Paris and our team is in 3x a week.
• Health insurance — Full coverage via Alan.
• Meal vouchers — Via Swile.
• Annual offsite — The whole team, once a year, somewhere worth the trip.
• Tech Syncs — Engineering and Product meet in person at least quarterly, worldwide.

What This Job Offers

• Job Type: Full-time
• Career Level: Director
• Education Level: No Education Listed