Lead Data Engineer / Applied ML (Hands-on) — Circular Economy
Lead an existing 2-person team · EU-Remote or Milan
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.
Picture your first 90 days
Week 2: You've mapped the data flows and agreed on a crisp, outcome-based roadmap.
Week 6: A reliable ELT path with data contracts and monitoring is live;
noise down, signal up.
Day 90: A production model (pricing/risk/catalog) is shipped with automated evals, drift alerts and a measurable lift.
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.
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