Data Engineer in Reading

We have an exciting opportunity for a Data Engineer to join our growing Data Platforms and Solutions Team. The successful applicant will work alongside our architects and consultants to deliver high quality data solutions (predominantly Azure-based) to help our customers become more successful in delivering the insight to maximise and scale automated decision making. Successful candidates can be based out of either of our Glasgow or Reading office, on a Hybrid working model.

Responsibilities

• Understand customer requirements and work collaboratively to design data solutions that deliver high quality outcomes.
• Enable higher quality data to be created & managed in our customers organisations.
• Develop high quality data products utilising (primarily) cloud native patterns.
• Engineer cloud-based data lake patterns to connect and leverage organisational & external data.
• Provide technical support and guidance through prototyping, testing, build, and launch of data products.
• Contribute towards the creation of technical support and design documentation for data platforms and solutions.
• Contribute to continually refining our development standards and best practices.

About you

• Strong technical expertise using core Microsoft Azure data technologies: Data Factory, Databricks, Data Lake, Azure SQL, Fabric, Synapse, Data Catalog, Purview.
• A strong background in Python development (for data engineering) and SQL.
• Proficient with Azure databases such as Synapse EDW, SQL Managed Instance, and Azure SQL.
• Skilled in Devops (CI/CD) implementations, including IaC deployments (Bicep, Terraform, etc.).
• Strong expertise in designing and building scalable data models to support business requirements.
• Adept at team collaboration and task tracking with Azure DevOps, adhering to Scrum/Agile methodologies.

Knowledge and experience of the following would be advantageous:

• Azure services used for infrastructure build and monitoring (ARM, Policy, Monitor, Log Analytics etc).
• Knowledge of data engineering within alternative cloud providers (AWS, GCP).
• Implementation of big data/analytics services.
• Supporting AI/Machine Learning workflows at production-level scale.
• NoSQL databases such as Cosmos DB or Mongo DB.
• Experience in working with Power BI, including Power Query, DAX, and Power BI Service.

What we look for in our people

• Strong alignment with FSP values and ethos.
• Commitment to teamwork, quality and mutual success.
• Proactivity with an ability to operate with pace and energy.
• Strong communication and interpersonal skills.
• Dedication to excellence and quality.

Why work for FSP?

• A collaborative and supportive environment in which you can grow and develop your career.
• The tools and opportunity to do work you can be proud of.
• A chance to work alongside some of the best people in the industry, who always seek to share their knowledge and experience.
• Hybrid working – we empower you to make smart choices about when and where to work to achieve great results.
• Industry leading coaching and mentoring.
• Competitive salary and an excellent benefits package.

Equal and Fair Opportunity

FSP is an equal opportunity employer, and we welcome applications from all suitable candidates. We consider all applicants for employment regardless of age, disability, sexual orientation, gender identity, family or parental status, race, colour, nationality, ethnic or national origin, religion or belief. Research suggests that applicants from underrepresented groups are less likely to apply for roles if they do not precisely meet requirements, or if they felt there were clear barriers as to who should apply. If you are excited about a potential role with us but are concerned that you may not be a perfect fit, please do apply, as you may be the ideal candidate for this role or for a different vacancy within FSP. We endeavour to always provide fair opportunity for applicants to showcase themselves in the best way possible during any interviews or meetings. If you require any adjustments for a call or in-person meeting, please let us know.