Senior Data Engineer

Senior Data EngineerYour new companyAn established and highly recognised organisation is investing heavily in its Data & Analytics capability to deliver on a well-defined AI strategy. Working within a collaborative Centre of Excellence (CoE), you will play a key role in building scalable data and AI solutions that drive customer-centric outcomes across the business.

This is an opportunity to work within a modern cloud-based data environment alongside technology, engineering, architecture, and analytics teams to deliver innovative data products and AI-driven capabilities.

Your new roleAs a Senior Data Engineer, you will report to the Data Engineering Manager and be responsible for designing, building, and optimising data pipelines that transform foundational data into highly reusable data products. These products will serve as a trusted source of truth across the organisation and support advanced analytics, AI, and machine learning initiatives.

Key responsibilities include

• Designing and developing scalable ETL/ELT and MLOps pipelines.
• Building and maintaining high-quality data engineering solutions and reusable data products.
• Developing and supporting modern data and AI platforms.
• Conducting code reviews and contributing to engineering best practices.
• Supporting continuous improvement initiatives across data engineering and AI capabilities.
• Troubleshooting and resolving data pipeline and platform issues.
• Ensuring BAU data products meet required service levels and operational standards.
• Collaborating with Data Scientists, ML Engineers, Analysts, Platform Engineers, Architects, and business stakeholders to deliver business value.
• Supporting agile delivery practices and contributing to the wider Data & Analytics strategy.
• What you'll need to succeed
• A degree in Computer Science, Engineering, Mathematics, or a related quantitative discipline.
• At least 5 years of hands-on experience in Data Engineering, Machine Learning Operations, or a similar field.
• Strong SQL and Python development skills.
• Experience building ETL/ELT pipelines and working with modern data architectures, including Data Lakes, Data Warehouses, Star Schemas, Change Data Capture, orchestration frameworks, and data observability tooling.
• Exposure to AI and machine learning platforms, including model deployment, orchestration, foundational models, integrations, and responsible AI practices.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
• Hands-on experience with modern data technologies such as Databricks, dbt, Airflow, and Amazon Redshift.
• Strong stakeholder engagement and collaboration skills within complex enterprise environments.A proactive problem-solving mindset with the ability to work effectively in ambiguous and evolving environments.
• Desirable experience includes:
• Software Engineering or DevOps experience.
• Knowledge of CI/CD, source control, Terraform, Java, or related technologies.
• Experience working within large-scale organisations across telecommunications, financial services, insurance, or retail sectors.
• What you'll get in return
• The opportunity to contribute to a large-scale AI and data transformation programme.
• Exposure to modern cloud, data, and AI technologies.A collaborative and high-performing engineering environment.
• The chance to work alongside experienced Data Engineers, Data Scientists, ML Engineers, and Analytics professionals.