Data Engineer - DV Cleared

In this role you will design and deliver data engineering and AI-focused solutions for clients, deploying ML models to production and ensuring monitoring, scalability, and robust data pipelines. You will work within a cross-functional team to implement ETL/ELT processes, data modelling, and data flows that support analytics and BI. You will stay current with AI/ML developments and contribute to client outcomes through effective communication and collaboration. This is a hands-on, client-facing position in a consultancy environment with a focus on delivering high-quality, scalable data and AI solutions.

• 25 days vacation
• private medical insurance
• 3 extra days leave per year for charitable work
• extensive benefits package

• Deploy machine learning models to production and monitor performance
• Build and orchestrate ETL pipelines for batch and streaming data
• Define and iterate data mappings using data modelling concepts
• Re-engineer data pipelines for scalability, automation, and repeatability
• Explore and query large-scale datasets
• Develop data transformation processes, metadata management, and workload control
• Identify and resolve data quality and mapping issues
• Connect operational data to analytics and BI systems
• Provide high-quality implementation and documentation for critical functionality
• Deliver code with tests and integration tests
• Work in an agile scrum team and participate in sprint rituals
• Collaborate with team to understand designs and triage issues
• Stay informed on latest tech developments, especially generative AI
• Lead a team and exercise decision-making when needed

• Strong proficiency in Python
• Extensive experience with cloud platforms (AWS, GCP, or Azure)
• Data warehousing and lake architectures
• ETL/ELT pipeline development
• SQL and NoSQL databases
• Distributed computing frameworks (Spark, Kinesis)
• Software development best practices including CI/CD, TDD, and version control
• Containerisation tools such as Docker or Kubernetes
• Infrastructure as Code (Terraform or CloudFormation)
• Strong data modelling and system architecture understanding
• Experience on at least one AI/ML project
• Knowledge of common ML frameworks and models
• Understanding of monitoring ML models in production
• Experience leading a team and making decisions

• Effective written and verbal communication
• Critical thinking and problem solving
• Stakeholder management and collaboration
• Python
• AWS, GCP, or Azure cloud platforms
• Data warehousing and lake architectures