Data Engineer

Social network you want to login/join with:

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:

• Collaborating with business subject matter experts to discover valuable insights in structured, semi-structured, and unstructured data sources.
• Using data engineering and AI techniques to help clients make smarter decisions, reduce service failures, and deliver better customer outcomes.
• Connecting to and extracting data from source systems, applying business logic and transformations, and enabling data-driven decision-making.
• Supporting strategic planning and identifying opportunities to apply AI models or machine learning techniques to enhance business processes.
• Capturing data requirements from customer and technical teams.
• Designing and implementing new data collection processes that ensure completeness, quality, and business relevance.
• Developing innovative ways of working to improve efficiency and scalability.
• Setting up interfaces to source systems and/or collaborating with system owners.
• Building, orchestrating, and optimisingdata and AI pipelines.
• Diagnosing root causes of poor data quality and working with data owners to resolve them.
• Securing and managing data access.
• Supporting data science teams and other users in data acquisition and preparation.
• Creating robust data models and deploying them into production.
• Ensuring 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.
• 25 Days holiday (excluding bank holidays) – increasing by a day every 2 years.
• Flexible working options – hybrid.
• Mental health and wellbeing support, including access to counselling.
• Annual wellbeing allowance (e.g. personal training, fitness, wellness apps).
• Up to 10% of your salary in employee benefits, including critical illness cover, life insurance, and private healthcare (post-probation).
• Generous company pension contribution.
• Ongoing professional development and training opportunities.

#J-18808-Ljbffr