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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