Data & AI Engineer

Overview

As a Data & AI Engineer at Accenture in Glasgow, you join a global Data & AI practice delivering large-scale data and AI solutions. You’ll work across cloud platforms, data pipelines, and AI-enabled delivery, applying GenAI tooling to accelerate engineering. You will collaborate with architects, product engineers and stakeholders to translate requirements into scalable data and platform solutions. This role offers a path to grow your technical breadth within a culture that values innovation and inclusion.

Pay / Benefits

• 25 days’ vacation per year
• private medical insurance
• 3 extra days’ leave per year for charitable work

Responsibilities

• Build and operate cloud data & platform solutions on Azure, AWS, GCP, Databricks, Microsoft Fabric or Snowflake
• Develop and maintain scalable batch and streaming data pipelines (ETL/ELT) to ingest, validate, cleanse and transform data
• Implement infrastructure as code to provision and manage cloud environments (Terraform, Bicep, CloudFormation)
• Create CI/CD pipelines for data/platform delivery using Git, Azure DevOps or GitHub Actions
• Apply data modelling principles (dimensional design, medallion architecture, S2T mapping) with AI tooling to draft and review models
• Implement data quality, lineage, observability and monitoring, leveraging automation and AI-assisted tooling
• Support cloud platform operations including networking, IAM, security and policy adherence
• Utilize GenAI and AI-assisted tools to accelerate development, testing and documentation with engineering judgement
• Develop an understanding of agentic AI concepts to inform design for autonomous/human-in-the-loop systems
• Collaborate with architects, product engineers and business stakeholders to meet technical and business needs

Key requirements

• Cloud engineering experience across one or more of: Azure, AWS, GCP, Databricks, Microsoft Fabric, Snowflake
• Python and SQL with strong engineering fundamentals
• Experience with batch and/or streaming data pipelines or cloud infrastructure/platform engineering
• CI/CD tooling for data/platform delivery (Git, Azure DevOps, GitHub Actions)
• Practical use of GenAI or AI-assisted development tools in daily work
• Awareness of AI-ready architecture concepts affecting reliability of AI/ML systems
• Basic understanding of agentic AI concepts and data/platform interdependencies

• Curiosity
• Driven technologist
• Willingness to learn and adapt
• Python
• SQL
• Azure, AWS, GCP, Databricks, Microsoft Fabric, Snowflake

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