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Accenture

Advises businesses and runs their technology

Data & AI Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-timeGlasgow, UKNo salary listed

About the Job

Requirements

  • Cloud engineering experience across one or more of Azure, AWS, Google Cloud Platform, Databricks, Microsoft Fabric, or Snowflake.
  • Python and SQL skills, with strong engineering fundamentals.
  • Experience developing batch or streaming pipelines, cloud infrastructure and platform engineering, or both.
  • Experience with continuous integration and continuous delivery tooling for data and platform delivery, such as Git, Azure DevOps, or GitHub Actions.
  • Practical use of generative AI or AI-assisted development tools in day-to-day engineering work.
  • Some familiarity with AI-ready architecture concepts, including how quality, latency, schema, security, and lineage affect downstream AI and machine learning systems.
  • A basic understanding of agentic AI concepts and how autonomous systems interact with and depend on data and platform infrastructure.

Responsibilities

  • Build and operate cloud data and platform solutions across modern cloud and data platforms.
  • Develop and maintain scalable batch and streaming data pipelines, applying extract, transform, and load/extract, load, and transform patterns to ingest, validate, normalise, cleanse, and transform data at scale.
  • Build and support cloud platform infrastructure using Infrastructure as Code tools, contributing to automated provisioning and management of cloud environments.
  • Implement continuous integration and continuous delivery pipelines for data and platform solutions, including AI-assisted approaches to automated testing and documentation.
  • Apply data modelling principles, including dimensional/Kimball modelling, medallion architecture, and source-to-target mapping, using AI tooling to draft and iterate models and critically review the outputs.
  • Implement data quality, lineage, observability, and monitoring capabilities, using automation and AI-assisted tooling to build scalable, self-describing pipelines and platforms.
  • Support cloud platform operations, including networking, identity and access management, security fundamentals, and policy adherence.
  • Use generative AI and AI-assisted development tools to accelerate engineering delivery by writing, testing, and documenting with AI assistance, and applying engineering judgement to validate and correct generated outputs.
  • Develop a working understanding of agentic concepts, including how autonomous and human-in-the-loop AI systems interact with data and platform infrastructure, to inform solutions designed for agentic consumption.
  • Collaborate with architects, product engineers, and business stakeholders to understand requirements and contribute to solutions meeting technical and business needs.
  • Spend time onsite with clients and partners as required to deliver services.

Desired Qualifications

  • Data modelling experience, including dimensional design, medallion architecture, or source-to-target mapping.
  • Hands-on experience building pipelines that support agentic workflows or large language model-based applications.
  • Familiarity with data product principles, including discoverability, reusability, quality contracts, and service-level agreements.
  • Hands-on experience with Decision Intelligence Platforms such as Palantir or Quantexa.
  • Infrastructure as Code experience with Terraform, Bicep, CloudFormation, or similar tools.
  • Cloud networking, identity, access management, or security engineering experience.
  • Familiarity with policy-as-code or platform governance controls.
  • Relevant cloud or data platform certifications, such as Azure Data Engineer Associate, AWS Data Analytics Specialty, Databricks Certified Associate Developer, or AWS Solutions Architect Associate.
  • AI or machine learning engineering certifications, such as Databricks Generative AI Engineer, AWS Machine Learning Specialty, or Google Professional Machine Learning Engineer.

About the Company

Accenture

Advises businesses and runs their technology

Accenture advises large businesses and public agencies on strategy, builds their technology systems and runs ongoing operations. Its teams connect business planning with implementation, covering areas such as cloud migration, cybersecurity and customer experience. Consultants work with clients to redesign processes, while engineers integrate software from technology partners and maintain the resulting systems for multinational organizations. Clients pay for project work or continuing services, including application support and business processes such as finance and customer service. Accenture was founded in 1989 and has its headquarters in Dublin, Ireland.

Company size
10,001+
Company stage
IPO
Headquarters
Dublin, Ireland
Founded
1989

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