Senior Data Engineer (12 months)

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.

Where do you come in?

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

As part of our data engineering capability a Senior Data Engineer will be responsible for inspiring and assisting Data Engineering team in designing, developing, and testing quality data engineering solutions, delivered through domain orientated multi-disciplined data product teams.

This role will act as a Data Engineering expert for the Data Office, also helping Data Engineering teams standardise and automate as much of their work as possible, to reduce waste and improve quality.

You will be continually challenging and improving our processes, tools, and methodologies, as well as coaching, developing, and mentoring other members of the team.

Role involves undertaking review and assurance activity, providing other team members with guidance on design, build and test activity and you will define outcomes and quality of work for 3rd parties and overseeing and supporting their deliveries.

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).

Do you have experience in Terraform?, You will have Data Engineering and/or DataOps related qualification and/or extensive Data/DataOps Development experience in a commercial & Agile environment. As well as proven technical leadership skills., * Strong experience in developing and automating scalable data pipelines in a Finance related data context with a DataOps mindset and evolved your expertise toward operational excellence and automation in data environments.

• In addition to a solid foundation in data engineering, you also demonstrate expertise in automation, CI/CD pipelines, IaC, monitoring systems to ensure scalable, reliable data workflows. You bring experience with the following tools:
• AWS data tooling such as (but not limited to) S3, Glue, Redshift, Lambda
• Familiarity with containerization (e.g., Docker/ec2), Orchestration in enterpirse environment, Infrastructure automation (Terraform), and CI/CD platform (Github Actions & Admin), Password/Secret management (hashicorp vault).
• Strong Data related programming skills SQL/Python/Spark/Scala.

Experience in these areas would be helpful:

• Experience of working in an Agile Team; preferably Safe.
• Experience in specific tooling Qlik Replicate / Qlik Compose / DataBricks / Informatica / SAS
• An understanding of data modelling methodology (Kimball, Data Vault, Lakehouse)
• Understanding of Data Science, AI and Machine Learning ways of working
• Experience of testing and testing standards.

Full time - 35 Hours