Senior Data Engineer - Data & AI Ops Lead

Royal London; Alderley Edge; Hybrid; GBP 90,000 - 120,000; Full time

Benefits offered by this job

28 days annual leave

Pension scheme up to 14%

Private medical insurance

Databricks certifications

Data Academy learning

Protected time for growth

Job summary

Royal London in Alderley Park is seeking a Senior Data Engineer to join our Data & AI Operations team. This role blends hands-on engineering with operational leadership to strengthen platforms that support data, AI, and automation across the organisation.

You will guide standards, coach colleagues, and help drive DataOps, AIOps and MLOps improvements while working in a hybrid setup with 50% home/office.

Qualifications

• Must have strong SQL, Python and PySpark experience.
• Experience across on-premises and cloud data environments.
• Knowledge of SQL Server technologies and CI/CD best practices.
• Experience of service management and incident management.
• Experience working in Agile delivery environments.
• Collaborative approach to coaching, mentoring and supporting others.
• Inquisitive mindset and enthusiasm for emerging AI technologies.

Responsibilities

• Set standards and promote best practice across Data & AI Operations.
• Lead continuous improvement of data pipelines and operational processes.
• Support DataOps, AIOps and MLOps activities across the team.
• Oversee operational monitoring and governance of AI solutions.
• Support implementation and optimisation of Databricks Genie and wider AI tooling.
• Lead service and incident management activities and contribute to change forums.
• Support sprint planning and workload management in an Agile environment.
• Coach and mentor junior colleagues and associate-level engineers.

Skills

SQL

Python

PySpark

On-prem & Cloud

CI/CD

Service Management

Agile Delivery

Coaching/Mentoring

AI Technologies

Tools

Databricks

Azure

AWS

Job description

Royal London in Alderley Park is seeking a Senior Data Engineer to join our Data & AI Operations team. This role blends hands-on engineering with operational leadership to strengthen platforms that support data, AI, and automation across the organisation.

You will guide standards, coach colleagues, and help drive DataOps, AIOps and MLOps improvements while working in a hybrid setup with 50% home/office.