BT Group
Data Engineer
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About BT
BT Group is the UK’s leading communications group and the holding company behind some of the country’s most recognised brands – including BT, EE, Openreach and Plusnet. Our purpose is as simple as it is ambitious: we connect for good. Our customers include consumers, small, medium and large businesses, public sector organisations and other communications providers.
BT Group’s role is about setting direction, unlocking value and creating the conditions for our brands and businesses to thrive.
Having come through the most capital-intensive phase of our fibre investment, our focus now is on what comes next – simplifying how we operate, using technology and AI to work smarter, and organising ourselves to serve customers better and grow sustainably. Group teams shape strategy, policy, brand, capital allocation and transformation, helping the whole organisation perform at its best.
We have a singular culture that unites all our people: we are customer-first challengers, who are committed, clear and connected. These behaviours unite us as one team to deliver for our colleagues, our customers, our stakeholders and the country. Joining BT Group means working at the heart of a business that matters to the UK, with the opportunity to shape decisions, influence outcomes and help set the future course of one of the country’s most important companies.
About the role
This role is central to enabling BT Group’s data driven decision making by shaping how structured and unstructured data is captured, managed, stored, and utilised across the organisation. The Data Engineering Professional translates business requirements into reliable, scalable data solutions that strengthen our overall data strategy. In addition to designing robust data processes and contributing to reusable engineering patterns, this role plays a hands-on part in the full delivery lifecycle – driving development, conducting thorough testing, and ensuring smooth deployment of high quality data pipelines and products. Through this, the role directly enhances the organisation’s ability to produce accurate, trustworthy, and impactful insights driven decision making by shaping how structured and unstructured data is captured, managed, stored, and utilised across the organisation.
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What you’ll need to succeed (Skills & Experience)
Must have
- Cloud (GCP): Hands on experience with key Google Cloud Platform services such as BigQuery, Cloud Storage, Cloud Composer, Dataflow, and Pub/Sub, with the ability to design, develop, optimize, and manage data pipelines and cloud native architectures.
- SQL: Proficiency in SQL, including writing complex queries, optimizing performance, handling large datasets, and implementing data validation and quality checks across analytical platforms.
- Data Warehousing: Experience in designing and implementing Data Warehouse solutions across different platforms, including schema design, ETL/ELT patterns and performance tuning.
- Programming (Python): Experience in Python for building data pipelines and automation using cloud services, APIs, and SDKs, with an understanding of modular coding, error handling, and reusable components.
- Terraform: Experience with Terraform for infrastructure as code; willingness and ability to learn quickly is essential.
- DevOps & Automation: Understanding of DevOps principles with hands-on experience in version control, CI/CD pipelines, automation, and defect management. Mandatory experience with GitLab for code management and deployments.
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Would be good to have
- Agile Methodology: Working knowledge of Agile delivery practices and tools such as Jira and Confluence, with the ability to collaborate in fast paced, iterative development cycles.
- Strong analytical and communication skills, with the ability to interpret complex data and present insights in clear, user friendly formats for technical and non-technical stakeholders.
- Experience managing deadlines and delivering high quality work under pressure in dynamic and fast-moving environments.
- Experience creating processes and documentation, including developing standard operating procedures, architectural diagrams, and technical documentation.
- Ability to work effectively with multiple stakeholders, collaborating across engineering, product, business, and operations teams to drive aligned outcomes.
- Experience in data quality frameworks, including implementing data validation, monitoring, and continuous improvement techniques.
- Familiarity with incident and service management tools such as ServiceNow for handling production issues, change management, and operational workflows.
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