Data and AI Engineer

Well-Safe Solutions, Aberdeen, though there may be a requirement to visit and work at other company locations or supplier’s premises as required.

The postholder must be able to attend our global headquarters in Aberdeen.

Job Type:

Permanent

Reporting Line:

The Data and AI Engineer will report directly to the Digital Solutions Lead and will work closely with stakeholders across Well Engineering, Project Teams, Finance, Operations and Corporate Functions.

Role:

The Data and AI Engineer will design, build and support secure, scalable data and AI solutions across Well-Safe Solutions, enabling reliable reporting, automation, knowledge discovery and data-driven decision-making.

The role will develop data pipelines, integrations, analytical data products and AI-enabled applications, translating business requirements into practical solutions under the direction of the Digital Solutions Lead.

Key responsibilities:

The Data and AI Engineer will be required to:

• Design, build, test and maintain data pipelines that ingest, transform and integrate data from operational, project, financial and corporate systems.
• Develop and maintain cloud-based data solutions using Microsoft Fabric and Azure services, including lakehouse, warehouse and data integration components where appropriate.
• Create reliable, reusable data models and curated datasets for Power BI, analytics, automation and AI use cases.
• Develop AI-enabled solutions such as enterprise search, knowledge assistants, document intelligence, summarisation and workflow automation, with human oversight and defined controls.
• Build prototypes and production-ready solutions using Python, SQL, APIs and relevant Microsoft technologies.
• Work with stakeholders to define use cases, assess feasibility, and technical designs.
• Establish monitoring, testing, version control, deployment and support practices for data and AI solutions.
• Improve data quality, lineage, metadata, documentation and ownership in line with company data governance requirements.
• Evaluate emerging data and AI technologies through controlled pilots, documenting benefits, risks, costs and recommendations.
• Independently deliver defined data engineering, AI and automation initiatives, escalating risks and decisions where appropriate.

Key outcomes:

• Reliable, secure and maintainable data pipelines and integrations with clear ownership and support arrangements.
• AI-enabled solutions that address defined business needs and operate within agreed governance, security and human-oversight controls.
• Reduced manual effort through practical automation of data, document and reporting processes.
• Improved data quality, accessibility, lineage and documentation across priority business domains.
• Increased stakeholder confidence and adoption through clear communication, training and dependable solution support.

Limits of authority:

Full responsibility for all operational activities within the philosophies and constraints laid out in the job description.

The company reserves the right to amend or change the activities listed, taking into account the job holder’s qualifications and experience to enable the business needs to be met.

Knowledge & Competency:

• Degree, HND or equivalent qualification in Computer Science, Data Engineering, Artificial Intelligence, Software Engineering, Information Systems, Mathematics, Engineering or a related discipline, or equivalent practical experience.
• Practical experience developing data pipelines, integrations or data platforms using SQL and Python.
• Experience with Microsoft Fabric, Azure data services or a comparable cloud data platform.
• Understanding of data modelling, ETL/ELT, APIs, data quality and structured and unstructured data processing.
• Experience applying software engineering practices including version control, testing, documentation and deployment.
• Practical understanding of AI and machine-learning concepts, including generative AI, retrieval-augmented generation, agentic, prompt design, evaluation and responsible use.
• Ability to translate business requirements into secure, maintainable technical solutions.
• Strong analytical, problem-solving, communication and stakeholder-engagement skills.
• Ability to manage priorities, work independently and collaborate effectively within a multidisciplinary team.
• Experience with Microsoft Fabric components such as Data Factory, Lakehouse, Warehouse, notebooks, OneLake or Power BI semantic models.
• Experience with Azure AI services, Azure OpenAI, AI Search, document intelligence or Microsoft Copilot Studio.
• Knowledge of MLOps, LLMOps, model evaluation, observability, vector databases or containerised application delivery.
• Experience with Power Platform, Power BI, DAX or Power Query.
• Knowledge of data governance, information security, privacy, responsible AI and records- management principles.
• Experience integrating engineering, operational or enterprise systems and working with complex technical data.
• Experience within the energy, engineering or industrial sectors.