Data Engineering Manager

Accenture UK & Ireland; Glasgow; On-site; GBP 110,000 - 140,000; Full time

Benefits offered by this job

30 days vacation

Private medical insurance

Volunteer leave

Job summary

Accenture UK & Ireland is seeking a Data Engineering Manager to lead cloud-scale data engineering programmes across platforms such as Azure, Databricks, Snowflake, and AWS. You will drive AI-assisted pipeline development, implement data quality and governance, and own end-to-end data product design while mentoring teams.

You will shape modern ETL/ELT migrations, architect observability and resiliency, and champion agentic AI patterns to accelerate delivery and value realization for complex

Qualifications

• Design and deliver cloud-scale data engineering solutions across cloud platforms.
• Experience with AI-assisted pipeline development and GenAI tooling.
• Strong data quality, observability, and governance capabilities.
• Proficiency in dimensional or Kimball data modelling and medallion architecture.
• Experience in ETL/ELT delivery and legacy-to-cloud migrations at scale.
• Ability to think in terms of data products and consumption-first models.
• Familiarity with agentic AI patterns in data pipelines.
• Proficiency in CI/CD and testing for data platforms.
• Proven track record of leading and mentoring engineering teams.

Responsibilities

• Lead delivery of cloud-scale data engineering programmes and platform migrations across multiple cloud environments.
• Drive AI-assisted pipeline development and governance of AI-generated outputs.
• Architect data quality, schema drift detection and lineage with AI-driven automation.
• Own data product design end-to-end from requirements to governance.
• Lead ETL/ELT modernisation and cloud migration initiatives.
• Define observability, resiliency and self-healing pipeline capabilities.
• Promote autonomous and human-in-the-loop AI operations within workflows.
• Translate data patterns into reusable agent skills and automation frameworks.
• Set CI/CD standards and testing practices for data platforms.

Skills

Cloud-scale data engineering

AI-assisted pipelines

Data quality & observability

Data modelling

ETL/ELT delivery

Data product thinking

Agentic AI patterns

CI/CD for data platforms

Leadership & mentoring

Tools

Azure

Databricks

Snowflake

GCP

Job description

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 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 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, Snowflake, AWS or GCP
• AI-assisted pipeline development — proven experience using GenAI tooling to accelerate engineering delivery and governing the quality of outputs
• Data quality, observability and automated governance — including schema drift detection, lineage management and AI-driven quality controls
• Data modelling including dimensional/Kimball design, medallion architecture and source-to-target mapping, with the ability to translate these into scalable, reusable patterns
• ETL/ELT delivery and legacy-to-cloud migration at scale
• Data product thinking — experience owning the full pipeline-to-product journey, with a consumption-first mindset and understanding of data product principles
• Agentic AI patterns in a data engineering context — experience designing or delivering pipelines that incorporate autonomous or human-in-the-loop AI workflows
• 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 driving delivery to a high standard

You should apply if

You don’t need to tick every box on this list. We’re looking for experienced data engineering leaders who have demonstrable depth across a number of these areas, and the technical curiosity to grow into the rest. If you set high standards, lead teams with purpose, embrace AI as a fundamental shift in how data engineering is practised — and want to work on some of the most ambitious data and AI programmes in the market — we want to hear from you.

Set yourself apart

• Hands-on experience designing or delivering agentic data pipeline capabilities or autonomous data operations in production
• Experience building reusable data product frameworks, templates or accelerators
• Demonstrable expertise with Decision Intelligence Platforms (e.g. Palantir, Quantexa)
• Experience contributing to commercial propositions, bids or client-facing accelerators
• Data modelling experience including dimensional design, medallion architecture or source-to-target mapping
• Familiarity with data product principles: discoverability, reusability, quality contracts and SLAs
• Relevant cloud or data platform certifications (e.g. Azure Data Engineer Associate, Databricks Certified Professional Data Engineer, AWS Data Analytics Specialty)
• AI platform and engineering certifications (e.g. Databricks Generative AI Engineer, AWS Machine Learning Specialty, Google Professional ML Engineer)
• AI practitioner certifications demonstrating hands‑on fluency with leading AI platforms — for example Anthropic Claude Certified Architect (CCAR-F or CCAR-P), Microsoft Agentic AI Business Solutions Architect (AB-100) or AI Agent Builder Associate (AB-620), or equivalent credentials from other leading AI vendors

What’s In It For You

At Accenture, in addition to a competitive basic salary, you will also have an extensive benefits package which includes 30 days’ vacation per year, private medical insurance and 3 extra days’ leave per year for charitable work of your choice!

Flexibility and mobility are required to deliver this role as there will be requirements to spend time onsite with our clients and partners to enable delivery of the first-class services we are known for.

Closing Date for Applications: 22/01/27

Accenture reserves the right to close the role prior to this date should a suitable applicant be found.