Role: Data & ML Engineer
Location: Newcastle Upon Tyne
Levels: Senior Analyst, Specialist

Experience Level: 3+ years

Please Note: Due to the nature of client work you will be undertaking, you will need to be willing to go through a Security Clearance (Including BPSS) process as part of this role, which requires 5+ years UK address history at the point of application.

Hybrid Working: Please note - This role will require you to work from our Newcastle, Cobalt Business Park office for a minimum of 3 days per week

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.

As a team:

Our Advanced Technology Centre is a thriving technology and innovation hub from where we deliver high quality services to a number of private and public sector clients.

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 part of our global team, you'll be working with cutting-edge technologies and will have the opportunity to develop a wide range of new skills on the job.

Role Overview:

As a Data & ML Engineer, you will design, build, and optimize scalable data pipelines and machine learning solutions. You’ll work with client teams to deliver intelligent data products, leveraging modern cloud and AI technologies.

Key Responsibilities

• Design and implement robust data pipelines and ML workflows using Python, SQL, Spark, and Databricks.

• Develop and deploy machine learning models (including NLP, deep learning, and agentic AI) in production environments.

• Integrate data from diverse sources, including streaming and batch ingestion, using Azure Data Factory, GCP Dataflow and AWS services.

• Apply data modelling concepts (e.g., medallion architecture) and ensure data quality and governance.

• Collaborate with DevOps teams to automate CI/CD and MLOps processes using Azure DevOps, Kubernetes, and Terraform.

• Visualize and communicate insights using Power BI, Tableau, and PowerApps.

• Mentor junior engineers and contribute to internal knowledge sharing.

• Ensure solutions meet security, compliance, and performance standards.