Lead Data Engineer / Applied Ml (Hands-On)

Overview

Lead Data Engineer / Applied ML (Hands-on) — Circular Economy

Lead an existing 2-person team

The hook

Own the data & ML engine behind a real-world re-commerce platform. 70% building, 30% leading. Ship pipelines and models that set prices, manage risk and match catalog, and feel your work move the business, every week.

What you’ll do (outcomes, not just tasks)

• Set the bar (Tech Lead) : Own architecture, standards and costs, so the team moves fast and safely.
• Level up people (Lead 2 → 3) : Mentor two engineers via reviews, 1 : 1s,and lightweight rituals that improve delivery.
• Data Engineering : Build / operate batch + streaming ELT; enforce data contracts, lineage, SLAs / SLOs to earn stakeholder trust.
• Applied ML : Train, validate and deploy models for pricing, risk and product matching; wire up A / B tests, drift & performance alerts and feedback loops.
• NLP & enrichment : Practical NLP (text cleanup, entity / product resolution) to boost search, classification and recommendations.
• Own production : Ship, measure, iterate, because value only counts in prod.

Stack you’ll touch (familiarity > checklists)

• Python, SQL
• Pandas / Polars
• Spark (nice)
• scikit-learn, PyTorch / TensorFlow, spaCy
• Warehouses / Lakes
• Orchestration & streaming
• Containers & CI / CD
• Cloud (AWS / GCP / Azure)
• IaC (plus)
• Plotly / Seaborn for exploration.

Signals you’re the one

• You’ve led small teams (or were the de-facto lead) and still love to code.
• You turn fuzzy problems into simple, reliable data / ML systems.
• You’ve shipped end-to-end : features → training → serving → monitoring.
• You care about quality, cost and reliability as much as accuracy.
• You write clearly and work async with Product & Backend without drama.

Nice to have

Fintech / marketplace / re-commerce exposure

• Streaming & feature stores
• Vector search / RAG
• Privacy & governance (PII, access control, lineage).

How we work (why this feels good)

• Autonomy + ownership : You make trade-offs, not slide decks.
• Fast feedback : Tight loop from idea → impact.
• Learning by shipping : Experiments beat ceremony, every time.

Offer & setup

Competitive salary + meaningful equity

• Milan (IT) hybrid or EU-remote
• Well-funded, product-obsessed environment.

Not for you if...

You want research-only or people-management-only. This is hands-on leadership.

Eligibility

BSc / MSc in CS / Engineering / Math (or equivalent).

How to apply (micro-ask) :

Send your CV + GitHub / LinkedIn and 2–3 lines on (1) a team you led and (2) a pipeline / model you shipped that moved a metric, because results matter.