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)