Data & AI Engineer — Cloud & Data Pipelines

Archer; Leeds; On-site; GBP 85,000 - 110,000; Full time

Benefits offered by this job

25 days vacation per year

Private medical insurance

3 extra days for charitable work

Job summary

Archer is partnering with Accenture to recruit a Data & AI Engineer for Leeds. The role focuses on building and operating cloud data solutions across Azure, AWS, GCP, and data platforms, delivering scalable pipelines and AI-assisted tooling.

You will implement IaC, CI/CD, data modelling and observability while collaborating with architects, product engineers and stakeholders to meet technical and business goals.

Qualifications

• Cloud engineering across 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 in day-to-day engineering work
• Familiarity with AI-ready architecture concepts — including awareness of how engineering decisions around quality, latency, schema, security and lineage affect reliability of downstream AI/ML systems
• A basic understanding of agentic AI concepts and how autonomous systems interact with data and platform infrastructure
• Collaborating with architects, product engineers and business stakeholders to understand requirements and contribute to solutions that meet both technical and business needs

Responsibilities

• Build and operate 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 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

Skills

Cloud engineering

Python

SQL

Batch & streaming pipelines

CI/CD tooling

GenAI

AI-assisted development tools

AI-ready architecture

Agentic AI concepts

Data platforms

Tools

Terraform

Bicep

CloudFormation

Databricks

Azure DevOps

GitHub Actions

Job description

Archer is partnering with Accenture to recruit a Data & AI Engineer for Leeds. The role focuses on building and operating cloud data solutions across Azure, AWS, GCP, and data platforms, delivering scalable pipelines and AI-assisted tooling.

You will implement IaC, CI/CD, data modelling and observability while collaborating with architects, product engineers and stakeholders to meet technical and business goals.