Lead Data Platform Engineer

Yazio

2d•Remote

About The Position

Yazio is entering a new phase where our data platform must support increasing scale, complexity and AI-powered product features. You, as the Lead of our Data Platform team will guide us through our next chapter: evolving it into the backbone for AI-driven personalization across a product used by over 2M people a day in 150+ countries. You'll lead a team of two senior engineers who know our product and our data inside out, and you'll take the platform from analytics enablement to AI-ready product infrastructure. In your first year, you'll: Mature the foundations of our Snowflake-based platform — clean SLOs, deeper observability, stronger reliability practices — so we can build confidently on top Design and ship the infrastructure for real-time and near-real-time feature serving, including training–serving consistency and feature freshness guarantees Set the platform engineering standards: SLAs, monitoring, incident practices, cost discipline. The bar you set becomes the bar the team operates to Partner with Pete and the Analytics team to draw clean ownership boundaries — Analytics owns "what & why" for features, you own "how & at what scale" Grow the team from two to roughly four engineers over the next 12 months, hiring against the bar you've set Run the day-to-day: planning, RFCs, incident response, technical mentorship. Hands-on where it counts

Requirements

Operated a cloud data platform at real scale — event ingestion, streaming, transformation, distributed systems — and you've seen what it takes to grow one 5–10x
Fluent in production reliability. SLOs, freshness guarantees, replay strategies and silent-failure detection aren't abstract concepts to you
Designed infrastructure for AI or ML in production — feature pipelines, online/offline stores, low-latency serving — not just used AI in your IDE
Led engineers before, even a small team. You know what good 1:1s and growth conversations look like, and you'd rather stay technical than become a pure manager
Think in trade-offs out loud — speed vs. cost, simplicity vs. flexibility, build vs. buy — and you take a position when you have enough data, even when it isn't perfect
See your job as making it easy for other teams to do the right thing. Contracts and tooling, not gatekeeping
Energised by working at a growth-stage company that's still figuring some things out — and you read that as opportunity, not chaos
Worked with Kafka, Spark and Snowflake in some form
CV in English

Nice To Haves

B2C consumer products at high traffic, especially mobile-first
Strong experimentation culture
Shipping a user-facing AI feature (not internal tooling) and being able to walk through the infrastructure decisions behind it
OKR ownership at team level
Came from GCP or self-hosted

Responsibilities

Mature the foundations of our Snowflake-based platform — clean SLOs, deeper observability, stronger reliability practices — so we can build confidently on top
Design and ship the infrastructure for real-time and near-real-time feature serving, including training–serving consistency and feature freshness guarantees
Set the platform engineering standards: SLAs, monitoring, incident practices, cost discipline.
Partner with Pete and the Analytics team to draw clean ownership boundaries — Analytics owns "what & why" for features, you own "how & at what scale"
Grow the team from two to roughly four engineers over the next 12 months, hiring against the bar you've set
Run the day-to-day: planning, RFCs, incident response, technical mentorship.