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Data Engineer

JR United Kingdom
Milton Keynes, England
7 months ago
Applications closed

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Posted
19 Oct 2025 (7 months ago)
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Due to continued growth, we are currently looking for a Data Engineer to join our Professional Services division. You will be part of a cross-functional Data Consulting team spanning data engineering, data science, AI, analytics, and visualisation.

You will work with clients across multiple sectors, helping them explore next-generation data techniques, AI capabilities, and tools to drive measurable business value from their data assets.

A day in the life of an Aiimi Data Engineer:

  • Collaborate with business subject matter experts to discover valuable insights in structured, semi-structured, and unstructured data sources.
  • Use data engineering and AI techniques to help clients make smarter decisions, reduce service failures, and deliver better customer outcomes.
  • Connect to and extract data from source systems, apply business logic and transformations, and enable data-driven decision-making.
  • Support strategic planning and identify opportunities to apply AI models or machine learning techniques to enhance business processes.
  • Capture data requirements from customer and technical teams.
  • Design and implement new data collection processes that ensure completeness, quality, and business relevance.
  • Develop innovative ways of working to improve efficiency and scalability.
  • Set up interfaces to source systems and collaborate with system owners.
  • Build, orchestrate, and optimise data and AI pipelines.
  • Diagnose root causes of poor data quality and work with data owners to resolve them.
  • Secure and manage data access.
  • Support data science teams and other users in data acquisition and preparation.
  • Create robust data models and deploy them into production.
  • Ensure models, reports, and architectures are promoted to centralised, self-service platforms.

Requirements

  • Collaboration: excited to work alongside subject matter experts, data scientists, AI specialists, analysts, and visualisation professionals.
  • Communication: able to explain complex technical concepts (including AI and machine learning outcomes) to non-technical audiences.
  • Problem Solving: using data and AI as a foundation to tackle business challenges.
  • Analytical Thinking: breaking down complex problems into manageable, actionable components.
  • Detail-Oriented: maintaining high-quality outputs under tight deadlines.
  • Lead by Example: inspiring clients to embrace new technologies, AI innovations, and modern data practices.
  • Adaptability: understanding legacy processes while introducing and championing new technology.

Technologies / Tools

  • Experience with Azure (ADF, Azure Databricks, Data Lake Storage, SQL DWH) or other cloud platforms (essential).
  • Familiarity with distributed systems (Spark, Databricks, etc.).
  • Familiarity with semi-structured and unstructured data formats.
  • Knowledge of machine learning frameworks and how to operationalise models in production.
  • Understanding of MLOps and AI model lifecycle management is a plus.


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