Senior AI Data Engineer
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)
