Data Berlin #30
Spring is back, and so is the Berlin data scene.
Spring is finally here in Berlin. The kind where everyone suddenly forgets winter ever happened, cafés are full at 11am on a Tuesday, and every patch of grass becomes a valid place to sit.
Alongside that, more interesting readings are being shared, meetups are picking up again, and the whole data scene feels a bit more alive.
If you work with data, you probably know the feeling. You open LinkedIn “just for a minute” and suddenly you are deep into job posts, dashboards, AI takes, and someone explaining why their new stack will change everything.
So to save you the scrolling, here’s a curated list of roles from this week.
The HandPicked Berlin Salary Trends Survey 2026 is open – Handpicked Berlin’s anonymous salary survey runs 1 Mar–1 Apr 2026, with a quicker flow on Tally and new topics (negotiation, office days, AI). Take the survey in Englihs or auf Deutsch; full details and past reports: 2026 overview.
We are all very curious to see the results.
📖Interesting Readings
Volume drops often show up only after data converges in the warehouse, so alerts should warn both upstream teams and downstream users, not just engineers – Where Is the Right Place to Catch Data Volume Anomalies?
Data hiring is still there but favors AI-related skills and production- or revenue-adjacent impact, so the practical move is to ship real work, get closer to money and decisions, blend disciplines, and prove value, not stay in generic “move data A→B” mode. – The Job Market Isn't Dead, But it Seems Far Pickier These Days
At companies like Uber, Netflix, and Airbnb, the semantic layer is platform infrastructure (metrics as code, centralized computation, APIs, governance, and quality), not a BI feature, and it increasingly doubles as the governed context layer for ML and AI agents. – Secrets of the Semantic Layer in Big Tech: How Uber, Netflix, and Airbnb Manage Metrics — and How You Can Apply It in Your Company
BI-as-code tools let you ship dashboards as SQL and Markdown in Git beside dbt models, so analytics gets diffs, portability, and the same PR workflow as the rest of your stack. – BI as Code for Data Engineers: Faster Analytics With SQL & Markdown
☕ Upcoming Meetups & Events
🧠 Hackathon – Data Berlin
If you are reading this newsletter on Monday the 23rd, today we are running the first Data Berlin Hackathon. Hosted by Snowflake and sponsored by Collate and Lightdash, with the support and a hack challenge from our friends at JustWatch.
We will report on it soon.
March 24 — How to Evaluate MCP-powered AI Agents Beyond Accuracy using Agent GPA — Berlin DataTalks Club🤖
April 28 — PyBerlin 60 – April Event🐍
💼 This Week’s Job Picks
🔎 Data Analyst
Senior Commercial Data Analyst — Moss → apply here
Senior Revenue Data Analyst — Wolt → apply here
Data Analyst (Revenue & AI) — Personio → apply here
Senior Data Analyst — Veeva Systems → apply here
⚙️ Analytics Engineer
Senior Analytics Engineer — Lovehoney Group → apply here
Analytics Engineer (OpenData EMEA) — Veeva Systems → apply here
Senior Analytics Engineer — Flink → apply here
Analytics Engineer (Pricing) — Octopus Energy → apply here
🏗️ Data Engineer
Senior Data Engineer — SumUp → apply here
Staff Data Engineer — Taxfix → apply here
(Senior) Data Engineer — Tieto → apply here
Data Engineer — Ottobock → apply here
🤖 AI / ML / LLM
Senior Data Scientist — Microsoft → apply here
Search Senior ML Engineer — Perplexity → apply here
AI/ML Engineer (Python) — Deel → apply here
Senior Data Scientist — Zoetis → apply here
Feels like things are picking up again.
More roles, more variety, and a bit more balance across the stack.
If you’re hiring or looking, feel free to reach out.
– The Data Berlin Team