Data Engineering Manager

Accenture; Glasgow; On-site; GBP 90,000 - 120,000; Full time

Job summary

Accenture in Glasgow is seeking an experienced Data Engineering Manager to lead the delivery of AI-powered data engineering initiatives. You will own the full data journey from pipeline design to data product delivery, guiding teams across Azure, Databricks, and Snowflake.

The role focuses on setting standards for AI-assisted development, data quality, and scalable pipelines while collaborating with cross-functional experts in a dynamic, global environment.

Qualifications

• Extensive track record delivering cloud-scale data engineering solutions.
• Experience leading data engineering teams in complex environments.
• Ability to design scalable data pipelines end-to-end.

Responsibilities

• Lead delivery of cloud-scale data engineering programmes across multiple cloud platforms.
• Drive AI-assisted pipeline development and govern AI-generated outputs.
• Design data quality, lineage and drift detection with AI-enhanced automation.
• Own data product design from requirements to governance for AI consumption.
• Lead ETL/ELT modernisation and cloud migration programmes.
• Architect observability, resiliency and self-healing pipelines with AI monitoring.
• Promote agentic pipeline patterns with autonomous and human-in-the-loop AI.
• Translate data models into reusable automation frameworks.
• Establish CI/CD and testing standards for data delivery with AI baselines.
• Mentor teams in AI-augmented data engineering practices.
• Contribute to propositions and reusable assets to speed future engagements.

Skills

Cloud data engineering

Data pipelines

AI-augmented delivery

Team leadership

Tools

Azure

Databricks

Microsoft Fabric

Snowflake

Job description

Data Engineering Manager

Location: Glasgow

Salary: Competitive Salary + Package (dependent on experience)

Accenture is a leading global professional services company, providing a broad range of services in strategy and consulting, interactive, technology and operations, with digital capabilities across all of these services. With our thought leadership and culture of innovation, we apply industry expertise, diverse skill sets and next-generation technology to each business challenge.

We believe in inclusion and diversity and supporting the whole person. Our core values comprise of Stewardship, Best People, Client Value Creation, One Global Network, Respect for the Individual and Integrity. Year after year, Accenture is recognized worldwide not just for business performance but for inclusion and diversity too.

"Across the globe, one thing is universally true of the people of Accenture: We care deeply about what we do and the impact we have with our clients and with the communities in which we work and live. It is personal to all of us." - Julie Sweet, Accenture CEO

As a team:

Working across industry groups, our Data & AI team combines deep technology, business and industry expertise to design and deliver some of the largest, most challenging and highest profile data and AI solutions in the world. We operate across Financial Services, Resources, Products, Communications and Health & Public Services.

Our practice is built around three strategic capabilities: AI Platform Engineering, AI Pipelines, and Data Products. Together these capabilities cover the full spectrum of modern data and AI delivery - from the cloud infrastructure and platforms that underpin AI workloads, through the pipelines that move and transform data at scale, to the data products that turn engineering effort into lasting business value.

As a Data Engineering Manager, you will lead delivery of AI-powered data engineering programmes - owning the full journey from pipeline design and build through to the data products that serve our clients' AI, analytics and business needs. We operate in an AI-augmented delivery model where AI-assisted pipeline development, automated data quality and agentic data operations are current practice, and our managers are expected to lead teams in adopting and embedding these approaches as standard.

You’ll learn, grow and advance in an innovative culture that thrives on shared success, diverse ways of thinking and enables boundaryless opportunities that can drive your career in new and exciting ways. If you're looking for a challenging career working in a vibrant environment with access to training and a global network of experts, this could be the role for you.

As a Data Engineering Manager, you will:

• Lead delivery of cloud-scale data engineering programmes and platform migration initiatives across Azure, Databricks, Microsoft Fabric, Snowflake, AWS and GCP
• Drive AI-assisted pipeline development as standard engineering practice - setting team norms around the use of GenAI tooling for pipeline build, testing and documentation, and governing the quality of AI-generated outputs
• Design and implement data quality, schema drift detection and lineage capabilities using AI-driven automation - moving teams away from manual quality gates towards intelligent, self-describing pipelines
• Own data product design and quality end to end - from consumption requirements through data modelling, pipeline delivery and ongoing governance - ensuring what the team builds is fit for business and AI consumption, not just technically correct
• Lead ETL/ELT modernisation and cloud migration programmes, applying AI-assisted approaches to accelerate analysis, mapping and delivery of legacy-to-cloud transitions
• Architect observability, resiliency and self-healing pipeline capabilities - using AI-driven monitoring and alerting to anticipate issues and reduce operational toil
• Drive adoption of agentic pipeline patterns - designing data workflows that incorporate autonomous and human-in-the-loop AI operations, and leading teams in understanding how to build, govern and iterate on these effectively
• Translate data modelling and mapping patterns into reusable agent skills and automation frameworks - moving the team beyond one-off delivery towards scalable, repeatable capability
• Establish CI/CD, testing automation and engineering standards across data engineering delivery, incorporating AI-assisted approaches as a baseline expectation
• Mentor and develop engineering teams in AI-augmented data engineering practices, setting technical standards and fostering a culture of continuous improvement
• Contribute to proposition development, accelerators and reusable data engineering assets that strengthen our market offering and reduce delivery time on future engagements

We are looking for significant experience in the following:

• Design and delivery of cloud-scale data engineering solutions across one or more of: Azure, Databricks, Microsoft Fabric, Snow