IT & Software

Data Engineering Manager

Accenture

Glasgow · Glasgow City · United Kingdom

Overview

In this role you lead cloud-scale data engineering programs and AI-driven data delivery, shaping data products for AI and analytics. You’ll guide teams through pipeline design, data modelling, and governance, leveraging AI-assisted practices to raise delivery quality. You work within a cross-functional Data & AI team to accelerate cloud migrations and platform enhancements. This is a hands-on leadership role at scale, with a focus on automating data quality and enabling autonomous data workflows in production.

Pay / Benefits
  • 30 days’ vacation per year
  • private medical insurance
  • 3 extra days’ leave per year for charitable work
Responsibilities
  • Lead delivery of cloud-scale data engineering programs and platform migrations across major cloud platforms
  • Drive AI-assisted pipeline development and establish norms for GenAI tooling in build, testing, and documentation
  • Design and implement AI-driven data quality, schema drift detection, and lineage capabilities
  • Own end-to-end data product design and governance from requirements to delivery
  • Lead ETL/ELT modernization and cloud migration initiatives with AI-assisted approaches
  • Architect observability, resiliency and self-healing pipelines with AI-driven monitoring
  • Advance agentic data patterns and human-in-the-loop AI operations in pipelines
  • Translate modelling patterns into reusable automation frameworks and skills
  • Establish CI/CD, testing automation and engineering standards for data delivery
  • Mentor engineering teams in AI-augmented data engineering practices
  • Contribute to propositions, accelerators and reusable data engineering assets
Key requirements
  • Experience designing and delivering cloud-scale data engineering solutions on Azure, Databricks, Microsoft Fabric, Snowflake, AWS or GCP
  • Proven AI-assisted pipeline development and governance of AI-generated outputs
  • Expertise in data quality, observability, lineage, and automated governance
  • Data modelling including dimensional design and medallion architecture with scalable patterns
  • ETL/ELT delivery and legacy-to-cloud migration at scale
  • Data product thinking from pipeline to consumption
  • Agentic AI patterns in data engineering with autonomous or human-in-the-loop workflows
  • CI/CD and engineering standards for data platforms with AI-assisted practices
  • Experience leading and mentoring engineering teams
  • leadership
  • mentoring
  • collaboration
  • Azure
  • Databricks
  • Microsoft Fabric

Reference: WJ-747_31050680

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