About this role
Salary: £61,000 - 101,000 per year
Requirements
- Significant experience designing and delivering cloud-scale data engineering solutions on one or more of Azure, Databricks, Microsoft Fabric, Snowflake, AWS or GCP.
- Proven experience using generative AI tools to accelerate engineering delivery and governing the quality of AI-generated outputs.
- Experience with data quality, observability and automated governance, including schema drift detection, lineage management and AI-driven quality controls.
- Data modelling experience, including dimensional/Kimball design, medallion architecture and source-to-target mapping, with the ability to develop scalable, reusable patterns.
- Experience delivering ETL/ELT and large-scale legacy-to-cloud migrations.
- Experience owning the pipeline-to-data-product lifecycle, with a consumption-first mindset and understanding of data product principles.
- Experience designing or delivering agentic AI patterns in data engineering, including autonomous or human-in-the-loop AI workflows.
- Experience establishing CI/CD and engineering standards for data platforms, including test automation and AI-assisted delivery practices.
- Experience leading and mentoring engineering teams, setting technical direction and maintaining high delivery standards.
- We welcome experienced data engineering leaders with demonstrable depth in several of these areas and the technical curiosity to develop in others.
- Additional strengths include production experience with agentic data pipelines or autonomous data operations; reusable data product frameworks, templates or accelerators; Decision Intelligence Platforms such as Palantir or Quantexa; commercial propositions, bids or client-facing accelerators; data product principles such as discoverability, reusability, quality contracts and SLAs; and relevant cloud, data platform, AI platform or AI practitioner certifications.
Responsibilities
- Lead delivery of cloud-scale data engineering programmes and platform migrations across cloud and data platforms.
- Make AI-assisted pipeline development standard practice, setting team norms for generative AI tools used in pipeline development, testing and documentation, and governing output quality.
- Design and implement data quality, schema drift detection and lineage capabilities using AI-driven automation and intelligent, self-describing pipelines.
- Own data product design and quality end to end, from consumption requirements and data modelling through pipeline delivery and ongoing governance.
- Lead ETL/ELT modernisation and cloud migration programmes, using AI-assisted approaches to accelerate legacy analysis, mapping and delivery.
- Architect observability, resiliency and self-healing pipeline capabilities, using AI-driven monitoring and alerting to anticipate issues and reduce operational effort.
- Drive adoption of agentic pipeline patterns, including autonomous and human-in-the-loop AI operations, and guide teams in building, governing and iterating on them.
- Turn data modelling and mapping patterns into reusable agent skills and automation frameworks.
- Establish CI/CD, test automation and engineering standards, incorporating AI-assisted practices.
- Mentor and develop engineering teams in AI-augmented data engineering, set technical standards and foster continuous improvement.
- Contribute to propositions, accelerators and reusable data engineering assets that strengthen our market offering and improve delivery efficiency.
Technologies
- Agentic AI
- AI
- AWS
- Architect
- Azure
- CI/CD
- Cloud
- Databricks
- ETL
- Fabric
- GCP
- Network
- Snowflake
- Machine Learning
- REST
More
We are a global professional services and technology consultancy, serving clients across more than 120 countries and combining technology, cloud, data and AI expertise with industry and functional experience. Our Data & AI team works across Financial Services, Resources, Products, Communications, and Health & Public Services, delivering complex data and AI solutions. This Data Engineering Manager role is based in Glasgow and offers a competitive salary dependent on experience, plus an extensive benefits package including 30 days of annual vacation, private medical insurance and three additional days of leave for charitable work.
The role requires flexibility and mobility, including time onsite with clients and partners. We foster inclusion, diversity, shared success, learning and career development, with access to training and a global network of experts. We make employment decisions without discrimination on grounds protected by applicable law.
last updated 46 week of 2026