MLOps Engineer (12 months)

About the role

Why should you come and work for a Data & Analytics Delivery department within a Building Society?

Well, we’re evolving and growing. And that brings changes to everything we do. We’re taking a good look at what we do and how we can do it faster. More efficient.

We build things here. We make things better. We don’t accept the status quo. It’s the way work should be, and perhaps a little bit of whatever you want.

We want you to help us make our evolution a success. Bring your experience. Bring your passion. Bring your drive. We want it all.

You will be designing, developing and testing quality machine learning and data engineering solutions as well as s upporting the development, deployment and monitoring of machine learning models and data pipelines. Role involves challenging and improving our processes, tools and approach, and undertaking review and assurance activity, providing other team members with guidance on design, build and test activity.

We operate on a team led hybrid approach with 2-3 days per week in the office.  Role requires travel to other sites for key meetings and collaborative working subject to business demand. Role is based in Coventry and involves some occasional out of hours working (within Society’s overtime policy).

About you

You will have either a Computer Science, Data Engineering related qualification and/or relevant career experience in MLOps, Machine learning and Data Engineering in a commercial & Agile environment.

For this role you’ll need to have:

• Strong Machine learning Operations and data engineering development experience
• You may have experience with the following tools:

• AWS data tooling such as S3/Glue/Redshift/SageMaker (Or relevant experience in another cloud technology).
• Specific tooling - Databricks
• Strong Data related programming skills SQL/Python/Spark
• Experience of industrialising and scaling machine learning models.
• Experience in deployment, monitoring, retraining and lifecycle management of ML models.
• Understanding of containerisation and infrastructure tooling (e.g., Docker, Kubernetes – exposure beneficial)
• Exposure to MLOps practices such as model lifecycle management, monitoring, observability, and pipeline automation.

Experience in these areas would be helpful:

• Experience of working in a Finance related data context.
• SAS and Informatica experience
• Scala
• Experience of working in an Agile Team
• An understanding of data modelling methodology (Kimball, Data Vault, Lakehouse)
• Experience of QA, testing automation, testing and testing standards.

Full time - 35 Hours

About us

If you are thinking about making an application but want to talk to someone first, you can reach out to [email protected] or the Talent Acquisition inbox [email protected]

This is a 12 month role and is at P1 Professional / Technical Grade in the IT Engineering job family

For all colleagues applying for our FTC roles, please note that this will be treated as a secondment opportunity.

Flexibility and why it matters.

We understand the need for flexibility, so wherever possible, we’ll consider alternative working patterns. Have a chat with us before you apply to see what the possibilities are for this role.

Proud to be a Disability Confident Committed Employer

We’re proud to offer an interview or assessment to every disabled applicant who meet the minimum criteria for our vacancies. As part of the application process, disabled applicants can opt in for the Disability Confident Interview Scheme. If there are ever occasions where it is not practicable to interview all candidates that meet the essential criteria, such as when we receive a high number of applications, we commit to interviewing disabled candidates who best meet the minimum essential and desirable criteria.

Location

Hybrid