Required skills
- Data Engineering
- ETL/ELT
- Data Lakehouse
- Feature Stores
- MLOps
- Agentic AI
- RAG
- Python
- SQL
- Spark
- PySpark
- CI/CD
- IaC
- APIs
Languages: German
Job description
Seeking a freelance Data & AI Engineer to develop scalable Lakehouse pipelines and Agentic AI solutions for an omnichannel retailer, bringing data-driven AI solutions from pipeline to production.
Project overview
Bring data-driven AI solutions from the pipeline directly into productive operation! For an omnichannel retailer, you will develop robust Data Lakehouse architectures, feature stores, and innovative Agentic AI applications. In this role, you will combine clean ETL/ELT pipelines with performant MLOps and create real added value for automated business processes.
Framework Data
Nice to have
Practical experience with Microsoft Azure (Azure OpenAI, AI Search, Data Factory) or Databricks (Delta Lake, Unity Catalog, MLflow)
Experience in developing Agentic AI (LLM orchestration with LangChain, LangGraph) as well as industry experience in e-commerce / retail
Are you currently available and does this match your skills? Then feel free to send me your CV with your hourly rate to *@*.de / [contact removed].
I look forward to your feedback!
Best regards
Pauline Reichenberger
Project details
01.11.2026
5 months (full-time)
Utilization: Full-time
Remote Share: Up to 100% remote
Language: German and English (fluent in spoken and written)
Activity
Conception and development of robust ETL/ELT pipelines and Data Lakehouse architectures (e.g., Medallion architecture) for integrating e-commerce, ERP, and store data
Setup and further development of feature stores and operationalization of machine learning models, including MLOps processes (training, deployment, monitoring, retraining)
Development of innovative Agentic AI and RAG solutions for automation and support of central business units
Provision of Data Products with clear quality standards and automation of infrastructure via CI/CD and IaC
Skills
Several years of practical experience in Data Engineering (ETL/ELT, Data Lakes, Data Warehouses, Lakehouse architectures)
Demonstrable experience in the productive operation of machine learning models and in building feature stores
Sound programming skills in Python and SQL, as well as practical experience with Spark / PySpark
Deep understanding of scalable system architectures, APIs, CI/CD pipelines, and automation
Negotiation-level German and English skills
- Start: 2026-11
- Duration: 5 Monate
- Remote: remote
- Location: Berlin, Deutschland, DE
- Languages: German
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