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Motius

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Senior Data Engineer (m/f/d)

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Summary

Senior Data Engineer in Munich who builds scalable data platforms, data warehouses, and advanced RAG pipelines powering the company's AI product, while mentoring engineers and improving data ingestion/QA. Core stack includes Azure/AWS/GCP, PySpark or Kafka, Redshift/Snowflake, and LLM tooling (RAG, fine-tuning, RLHF).

Overview

In this role, you will build scalable data platforms and advanced RAG pipelines powering our AI product. You’ll collaborate with AI engineers and cross-functional teams to bring cutting-edge reasoning models to life. You’ll visualize data, mentor peers, and improve data ingestion and QA processes. This position sits at the frontline of integrating AI features into customer-facing products and shaping our data architecture for rapid growth.

Leistungen / Benefits
  • learning & development budget
  • Talent Journey for growth
  • flexible working hours
  • up to 50% remote work
  • Tech Discovery and Discovery Conference
  • team buildings and company events
Verantwortungsbereiche
  • Build scalable data platforms, data stores/warehouses and RAG pipelines for AI systems
  • Collaborate with AI engineers to design and test innovative AI reasoning ideas using our ontology and data
  • Visualize data with dashboards and analytics solutions; mentor engineers on data engineering best practices
  • Improve QA and data ingestion processes with new tools and frameworks
  • Collaborate with stakeholders (AI Engineers, Product Managers, Chief Officers, Software Teams) to integrate AI features into products
Zentrale Anforderungen
  • University degree in Computer Science, Software Engineering, Data Science/Engineering or related disciplines
  • 4+ years of experience in agile development
  • Experience with data engineering for ML/AI production deployment/MLOps on cloud platforms (Azure, AWS and/or GCP)
  • Designing architectures for data platforms and data processing pipelines (batch and real-time) using PySpark or Kafka
  • Experience with data warehousing services (AWS Redshift, Snowflake), LLM data stores, SQL/no-SQL tools
  • Strong analytical and problem-solving skills; comfortable with ambiguity and rapid changes in early-stage product development
  • Experience with AI tools and LLM providers; implementing advanced RAG pipelines (e.g., GraphRAG); multi-agent architectures; ML model training; LLM fine-tuning; RLHF
  • Excellent verbal and written English communication; cross-functional collaboration
  • analytical thinking
  • adaptability to ambiguity
  • effective communication
  • Azure/AWS/GCP cloud platforms
  • PySpark
  • Kafka

Skills

What Senior Data Engineering jobs ask for — and how much of it you have →

See also

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