Data Engineer

🚀 Data Engineer | Azure Data & AI, Databricks, PySpark | AI Incubator Platform

🌍 Remote | 📄 B2B Contract |

We are looking for a detail-oriented Data Engineer with strong Data Science and Machine Learning lifecycle awareness to join our client's team—an in-house technology consultancy at a global consulting firm. You will design, build, and operate scalable, production-ready data pipelines for advanced analytics and NLP/NLU models, scouting and prototyping cutting-edge solutions across a 3–5 year horizon.

What You’ll Be Doing:

• Building, hardening, and maintaining reliable data ingestion and ETL/ELT pipelines for enterprise data platforms.
• Developing large-scale data processing and transformation workflows using Databricks and PySpark.
• Operating and integrating Azure data and AI infrastructure, including Blob Storage, compute resources, MLflow, and Azure AI/ML services.
• Preparing high-quality datasets, feature pipelines, and data architectures to support downstream NLP, NLU, and generative AI use cases.
• Implementing CI/CD and MLOps practices, including automated testing, deployment pipelines, observability, monitoring, and quality promotion gates.
• Taking end-to-end ownership of data quality, lineage tracking, and operational handovers for production-ready data products.

What We’re Looking For:

• Proven commercial experience in Data Engineering, large-scale data transformation, and production pipeline deployment.
• Strong Data Science and ML lifecycle awareness with the ability to bridge data engineering workflows with model experimentation and production deployment.
• Consultant mindset: proactive problem-solving, architectural ownership, and clear communication with cross-functional technical teams.
• Experience with pipeline observability, schema design, data quality validation, and lineage tracking.

Must-Haves:

• Strong programming and data processing skills in Python and PySpark.
• Hands-on expertise with Databricks for distributed data engineering and scalable workflow orchestration.
• Practical experience with the Azure ecosystem (Azure Blob Storage, Azure SQL/Databases, compute resources, MLflow, Azure AI/ML services).
• Solid track record supporting NLP/NLU workflows and preparing structured datasets for machine learning applications.
• Strong English communication skills for daily international collaboration.

Location & Working Setup:

• 100% Remote working model (Candidates must be living and working within the EU).
• US Hours overlap needed: Standard work hours by 6:00 PM CET (Typically 10:00 AM – 6:00 PM or 11:00 AM – 7:00/8:00 PM CET).
• Availability for occasional in-person team workshops/gatherings (approx. 1x per quarter in Prague).

Ready to build the data foundation for next-generation AI platforms? Apply today or send your CV directly to discuss the details!