DataOps Engineer (12 months fixed term)

Coventry Building Society is undergoing an exciting period of transformation and growth, with Data & Analytics playing a key role in driving innovation and delivering value across the business. The team is focused on building smarter, more efficient ways of working, continuously improving processes, and delivering high-quality data solutions that make a real impact.

As a DataOps Engineer (12 months fixed term) , the role holder will support the design, development and testing of data engineering solutions within multidisciplinary data product teams. Acting as a CI/CD specialist for the Data Office, the person in post will help automate data engineering processes, improve delivery quality, and drive continuous improvement across tools, methodologies and ways of working.

The role also offers opportunities to coach and support colleagues, provide technical guidance and assurance, work with third-party suppliers, and contribute to the ongoing support of business-critical data solutions, including occasional out-of-hours activities.

We operate a team-led hybrid approach, with colleagues typically spending 1-2 days per week in our Coventry or Manchester office.

Our benefits include:

• 28 days holiday a year plus bank holidays and a holiday buy/sell scheme
• Annual discretionary bonus scheme
• Personal pension with matched contributions
• Life assurance (6 times annual salary)

We reserve the right to close this advert early if we receive a high volume of suitable applications.

About you

We're looking for a passionate and technically skilled DataOps Engineer to join our growing Data & Analytics team. You'll play a key role in delivering modern, scalable data solutions, driving automation and continuous improvement, and helping to shape best practices across our data engineering capability. This is an exciting opportunity to work with cutting-edge technologies while making a real impact on the Society's data transformation journey.

For this role you’ll need to have:

• AWS Data tooling such as S3/Glue,Redshift.
• Familiarity with containerization (e.g. Docker/ec2), Orchestraion in enterprise environment (Airflow), Infrastructure automation (Terraform), and CI/CD platform (Github Actions and Admin), Password/Secret Management (hashicorp vault).
• Strong Data related programming skills SQL/Python/Spark/Scala.
• Database technologies in relation to Data Warehousing /Data Lake/ Lake housing patterns and relevant experience when handling structured and non-structured data.
• (Information Modeler) Experience in data modelling techniques and tooling.
• (Test) Quality Assurance and Test Automation experience in a Data Pipeline.

Experience in these areas would be helpful:

• Experience working within Agile teams, ideally using SAFe methodologies.
• Knowledge of tools such as Qlik Replicate, Qlik Compose, Databricks, Informatica, or SAS.
• Understanding of data modelling methodologies, including Kimball, Data Vault, and Lakehouse.
• Awareness of Data Science, AI, and Machine Learning principles and practices.
• Experience with testing frameworks, standards, and quality assurance practices.
• Experience deploying, industrialising, and scaling Machine Learning models.
• Hands-on experience with Machine Learning frameworks such as TensorFlow or PyTorch.
• Experience leading, coaching, and mentoring colleagues, with oversight of data product delivery within an Agile environment.

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