Data & AI Engineer

Data & AI Engineer

Location: Bristol

Salary: Competitive Salary + Package (dependent on experience)

Career level : Specialist/Consultant

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 & AI Engineer, you will join as an entry point into this capability, working across our three areas and developing your skills and specialisms as you grow. Our engineers work in an AI-augmented delivery model — using GenAI tooling as part of everyday engineering practice, applying AI-assisted approaches to how we design, build, test and document, and creating data and platform foundations that are ready for the AI and agentic systems our clients are building and running.

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 & AI Engineer, you will work across the following:

Building and operating cloud data and platform solutions across modern cloud and data platforms including Azure, AWS, GCP, Databricks, Microsoft Fabric and Snowflake

Developing and maintaining scalable batch and streaming data pipelines, applying ETL/ELT patterns to ingest, validate, normalise, cleanse and transform data at scale

Building and supporting cloud platform infrastructure using Infrastructure as Code tools such as Terraform, Bicep or CloudFormation, contributing to the automated provisioning and management of cloud environments

Implementing CI/CD pipelines for data and platform solutions using Git, Azure DevOps or GitHub Actions, including AI-assisted approaches to automated testing and documentation as part of standard delivery practice

Applying data modelling principles — including dimensional/Kimball, medallion architecture and source-to-target mapping — using AI tooling to draft and iterate models, with the ability to critically review outputs for correctness and fitness for purpose

Implementing data quality, lineage, observability and monitoring capabilities, applying automation and AI-assisted tooling to build scalable, self-describing pipelines and platforms

Supporting cloud platform operations including networking, identity and access management, security fundamentals and policy adherence

Using GenAI and AI-assisted development tools to accelerate engineering delivery — writing, testing and documenting with AI assistance and applying engineering judgement to validate and correct generated outputs

Developing a working understanding of agentic concepts — including how autonomous and human-in-the-loop AI systems interact with data and platform infrastructure — to inform how you design and build solutions that are fit for agentic consumption

Collaborating with architects, product engineers and business stakeholders to understand requirements and contribute to solutions that meet both technical and business needs

We are looking for experience in the following:

Cloud engineering across one or more of: Azure, AWS, GCP, Databricks, Microsoft Fabric or Snowflake

Python and SQL, with strong engineering fundamentals

Batch and/or streaming pipeline development, or cloud infrastructure and platform engineering — or both

CI/CD tooling for data and platform delivery (Git, Azure DevOps, GitHub Actions)

Practical use of GenAI or AI-assisted development tools (e.g. GitHub Copilot, Cursor, Databricks Assistant or similar) in day-to-day engineering work

Some familiarity with AI-ready architecture concepts — including awareness of how engineering decisions around quality, latency, schema, security and lineage affect the reliability of downstream AI and ML systems

A basic understanding of agentic AI concepts and how autonomous systems interact with and depend upon data and platform infrastructure

You should apply if:

You don’t need to tick every box on this list. We’re looking for curious, driven technologists who have demonstrable experience across a number of the skills and technologies above, and the appetite to grow into the rest. If you relish a challenge, embrace learning as part of your everyday work, and want to be part of a team that pushes boundaries and holds itself to a high standard — we want to hear from you.

Set yourself apart with one or more of the following:

Data modelling experience including dimensional design, medallion architecture or source-to-target mapping

Hands-on experience building pipelines that support agentic workflows or LLM-based applications

Familiarity with data product principles: discoverability, reusability, quality contracts and SLAs

Hands-on experience with Decision Intelligence Platforms (e.g. Palantir, Quantexa)

Infrastructure as Code experience (Terraform, Bicep, CloudFormation or similar)

Cloud networking, identity, access management or security engineering experience

Familiarity with policy-as-code or platform governance controls

Relevant cloud or data platform certifications (e.g. Azure Data Engineer Associate, AWS Data Analytics Specialty, Databricks Certified Associate Developer, AWS Solutions Architect Associate)

AI or ML engineering certifications (e.g. Databricks Generative AI Engineer, AWS Machine Learning Specialty, Google Professional ML Engineer)

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 25 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.

About Accenture

Accenture is a global professional services company with leading capabilities in digital, cloud and security. Combining unmatched experience and specialised skills across more than 40 industries, we offer Strategy and Consulting, Interactive, Technology and Operations services — all powered by the world’s largest network of Advanced Technology and I