Job
- Level
- Senior
- Ort
- Berlin
- Arbeitsmodell
- Hybrid, Onsite
- Job Feld
- Data, Back End
- Anstellung
- Vollzeit
- Vertragsart
- Unbefristetes Dienstverhältnis
Job Zusammenfassung
In dieser Rolle übernimmst du die Verantwortung für das Databricks-Lakehouse und modellierst vertrauenswürdige Datensätze für Finanzen, Vertrieb und Logistik, während du Datenpipelines baust und Monitoring-Systeme implementierst.
Job Technologien
Deine Rolle im Team
- Own our Databricks lakehouse end to end: ingestion from Salesforce and our operational systems, storage, pipeline architecture, orchestration and governance.
- Model the commercial and logistics domain (quotes, orders, margins, suppliers, shipments) into clean, trusted datasets that finance, sales, procurement and logistics can all use without keeping their own version of the truth.
- Work closely with our Head of Data to turn business questions into reusable datasets and metrics, not one-off exports.
- Build the data foundation for pricing, forecasting and our AI agents: features, signals, historical snapshots and feedback loops that tell us whether a decision was right.
- Make data quality observable: tests, monitoring and alerting, so broken pipelines and silent schema drift get caught before a buyer notices.
- Add near-real-time processing where the business needs to act now, and keep things simple where batch is enough.
Unsere Erwartungen an dich
Qualifikationen
- You've used a CRM or ERP as a primary source system and know what it means to model messy operational data that people edit by hand.
- Comfortable with infrastructure as code and with software engineering practices for data (version control, CI, testing).
- You talk to non-technical stakeholders easily and push back when a request should be solved differently.
- You work well in a Series B setting where priorities shift and nobody hands you a finished spec.
- You use AI coding tools as a natural part of your work and know where they help and where they don't.
Erfahrung
- 5+ years in data engineering, with real ownership of a platform rather than a single pipeline.
- Deep SQL and Python, plus hands-on experience with Spark and a lakehouse (Databricks strongly preferred: Delta Lake, Workflows, Unity Catalog).
Unser Angebot
- A growing 12-person product and engineering team where you own your area end to end.
- A company where data work is not a support function: our agents and our margin depend on it directly.
- Hybrid setup in Berlin.
- Direct access to the founders and to the commercial teams whose problems you are solving.
Themen mit denen du dich im Job beschäftigst
Job Standorte
Das ist dein Arbeitgeber
Andercore
Andercore ist ein modernes Unternehmen mit Sitz in Berlin, das sich auf den KI-gestützten Handel und die Distribution von industriellen Materialien konzentriert. Es beliefert europäische Kunden mit Materialien aus den Bereichen Energie, Infrastruktur und Bau und setzt dabei eigene KI-Technologien ein, um den Handelsprozess zu optimieren.
Description
- Unternehmenstyp
- Startup
- Arbeitsmodell
- Hybrid, Onsite
- Branche
- Industrie, Produktion
Senior Data Platform Engineer
- Ort
- Berlin
- Arbeitsmodell
- Hybrid, Onsite
- Diversität
- Für alle Personen geeignet (m/w/d)
- Nur Englisch
- Nur Englisch erforderlich
