Data Engineer (AI / ML)

Join to apply for the Data Engineer (AI / ML) role at Satalia.

Satalia, a WPP company, pushes the boundaries of data science, optimisation and artificial intelligence to solve complex industry problems. We are a community of individuals devoted to diverse projects, allowing you to flex your technical skills while working with a tight‑knit team of high‑performing colleagues.

Data Engineer (AI / ML). Permanent. Location: UK or Greece. Preferred start date: ASAP.

We are investing massively in developing next‑generation AI tools for multimodal datasets and a wide range of applications. We build large‑scale, enterprise‑grade solutions for FTSE 100 clients. As a member of our team, you will collaborate with world‑class talent and shape cutting‑edge AI products and services.

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• Collaborate closely with data scientists, architects, and other stakeholders to understand and break down business requirements.
  
• Collaborate on schema design, data contracts, and architecture decisions, ensuring alignment with AI/ML needs.
  
• Provide data engineering support for AI model development and deployment, ensuring data scientists have access to the data they need in the format they need it.
  
• Leverage cloud‑native tools (GCP / AWS / Azure) for orchestrating data pipelines, AI inference workloads, and scalable data services.
  
• Develop and maintain APIs for data services and serving model predictions.
  
• Support the development, evaluation and productionisation of agentic systems with:
  
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  • LLM‑powered features and prompt engineering
    
  • Retrieval‑Augmented Generation (RAG) pipelines
    
  • Multimodal vector embeddings and vector stores
    
  • Agent development frameworks: ADK, LangGraph, Autogen
    
  • Model Context Protocol (MCP) for integrating agents with tools, data and AI services
    
  • Google's Agent2Agent (A2A) protocol for communication and collaboration between different AI agents
    
  
  
  
• Implement and optimise data transformations and ETL/ELT processes, using appropriate data engineering tools.
  
• Work with a variety of databases and data warehousing solutions to store and retrieve data efficiently.
  
• Implement monitoring, troubleshooting, and maintenance procedures for data pipelines to ensure the high quality of data and optimise performance.
  
• Participate in the creation and ongoing maintenance of documentation, including data flow diagrams, architecture diagrams, data dictionaries, data catalogues, and process documentation.
  

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• High proficiency in Python and SQL.
  
• Strong knowledge of data structures, data modelling, and database operation.
  
• Proven hands‑on experience building and deploying data solutions on a major cloud platform (AWS, GCP, or Azure).
  
• Familiarity with containerisation technologies such as Docker and Kubernetes.
  
• Familiarity with Retrieval‑Augmented Generation (RAG) applications and modern AI/LLM frameworks (e.g., LangChain, Haystack, Google GenAI, etc.).
  
• Demonstrable experience designing, implementing, and optimizing robust data pipelines for performance, reliability, and cost‑effectiveness in a cloud‑native environment.
  
• Experience in supporting data science workloads and working with both structured and unstructured data.
  
• Experience working with both relational (e.g., PostgreSQL, MySQL) and NoSQL databases.
  
• Experience with a big data processing framework (e.g., Spark).
  

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• API Development: Experience building and deploying scalable and secure API services using a framework like FastAPI, Flask, or similar.
  
• Experience partnering with data scientists to automate pipelines for model training, evaluation, and inference, contributing to a robust MLOps cycle.
  
• Hands‑on experience designing, building, evaluating, and productionising RAG systems and agentic AI workflows.
  
• Hands‑on experience with vector databases (e.g., Pinecone, Weaviate, ChromaDB).
  

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• Benefits – enhanced pension, life assurance, income protection, private healthcare.
  
• Remote working – cafe, bedroom, beach – wherever works.
  
• Truly flexible working hours – school pick‑up, volunteering, gym.
  
• Generous Leave – 27 days holiday plus bank holidays and enhanced family leave.
  
• Annual bonus – when Satalia does well, we all do well.
  
• Impactful projects – focus on bringing meaningful social and environmental change.
  
• People‑oriented culture – wellbeing is a priority, as is being a nice person.
  
• Transparent and open culture – you will be heard.
  
• Development – focus on bringing the best out of each other.
  

Satalia is home to some of the brightest minds in AI and if you’re looking to join a company that not only values autonomy and freedom, but embraces a culture of inclusion and warmth, we’d love to hear from you.

We aim to respond to all applications within 2 weeks. If you have not heard from us within 2 weeks this means your application has been unsuccessful.

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Good luck!