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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:
- 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 optimising data 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
- SQL coding skills (essential).
- Python coding skills (essential).
- 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.
Benefits:
- 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.
