Data Engineer (m/w/d) - Big Data | KI/AI | ANÜ

About

Für unseren Kunden aus der Finanz‑IT‑ und Bankenbranche suchen wir Unterstützung durch einen Data Engineer (m/w/d) im Umfeld hochskalierbarer Datenplattformen. Im Fokus steht die Verarbeitung und Optimierung sehr großer Datenmengen (Big Data) für daten‑ und KI‑getriebene Anwendungsfälle. Gesucht wird ein erfahrener Profi mit starkem technischem Fokus auf Performance, Skalierung und Cloud‑Architekturen. Das Projekt ist langfristig ausgelegt und fachlich anspruchsvoll.

Project Details

• Start: ASAP
• Duration: until 31.12.2026 (option for extension possible)
• Location: Aschheim (near Munich)
• Remote Share: approx. 2-3 days per week remote
• Workload: 40 hours / week
• Contract Type: Temporary employment (Arbeitnehmerüberlassung)

Responsibilities

• Development and optimization of scalable data models for Big Data environments in the TB range
• Setup, operation, and continuous development of databases, especially PostgreSQL
• Ensuring performance, stability, and scalability for several thousand parallel users
• Conception, implementation, and optimization of robust ETL and data pipelines
• Processing extremely large datasets (sometimes 100+ billion records, continuous data flow)
• Close collaboration with Data Scientists, Software Developers, and Business Departments
• Support of AI/KI use cases based on large, growing data stocks
• Performance analyses and database tuning in production environments

Requirements

Must-haves

• Several years of experience as a Data Engineer in building scalable data architectures
• Very good SQL skills and in-depth experience with PostgreSQL
• Python experience in a production data and ETL environment
• Demonstrable practical experience with very large datasets (TB level and above)
• Experience with distributed systems and rapidly growing data volumes
• Sound knowledge in performance optimization and database scaling
• At least 3 years of experience in the AI/KI field with large datasets
• Experience with cloud technologies, ideally Microsoft Azure

Nice-to-haves

• Experience in an agile environment (Scrum, Kanban)
• Strong analytical thinking skills
• Structured, self-directed way of working
• Excellent team and communication skills