We are seeking a Senior AI Data Engineer to design, build, and maintain scalable data platforms and AI-ready data pipelines that power machine learning, generative AI, analytics, and business intelligence solutions. The ideal candidate combines strong data engineering expertise with a solid understanding of machine learning workflows, MLOps, and modern AI technologies.

The role involves collaborating with data scientists, programmers, and business stakeholders to deliver reliable, high-quality data solutions that enable AI-driven products and decision-making.

Your Key Responsibilities:

Data Engineering & Architecture

• Design, develop, and optimize scalable batch and real-time data pipelines;
• Build and maintain data lakes, data warehouses, and modern data platforms;
• Implement data modeling, transformation, validation, and governance processes;
• Ensure data quality, reliability, security, and compliance across systems;
• Optimize data storage, processing performance, and cost efficiency.

AI & Machine Learning Enablement

• Develop data infrastructure supporting machine learning and generative AI applications;
• Create feature engineering pipelines and feature stores;
• Support model training, deployment, monitoring, and retraining workflows;
• Integrate vector databases, embedding pipelines, and retrieval systems for GenAI applications;
• Collaborate with Data Scientists and ML Engineers to operationalize AI solutions.

Cloud & Platform Engineering

• Design cloud-native data solutions on AWS, Azure, or Google Cloud;
• Implement infrastructure-as-code and automation practices;
• Build CI/CD pipelines for data and AI workloads;
• Monitor system performance and troubleshoot production issues.

Leadership & Collaboration

• Participate in architecture reviews and strategic technology decisions;
• Collaborate with product managers and business stakeholders to define requirements;
• Promote engineering best practices and data governance standards.

A Successful Candidate Must Have:

• 5+ years of Data Engineering experience;
• 2+ years working with AI/ML platforms or AI-powered products;
• Strong Python and SQL skills;
• Hands-on experience with ClickHouse in production;
• Experience building large-scale ETL/ELT pipelines;
• Strong knowledge of cloud platforms (AWS, Azure, or GCP);
• Experience with Spark, Databricks, Kafka, and workflow orchestration tools (Airflow, Dagster, or Prefect);
• Understanding of data warehousing, data modeling, and distributed systems.

Extra Great to Have:

• Experience with vector databases (Qdrant, Pinecone, Weaviate, Milvus);
• Knowledge of LLMs, RAG architectures, MLOps, MLflow, Kubeflow, or cloud ML platforms;
• Experience with Docker, Kubernetes, Terraform, and modern CI/CD practices.

Salary: From 3310 EUR/month (gross)