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.RequirementsCollaboration:

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 / ToolsExperience 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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