Data Engineer (Enterprise Data & Intelligence)
Indexed description
Interested in joining our smart, fun, and talented team?
Position Overview
As a Data Engineer on the Enterprise Data & Intelligence team, you will design, build, and maintain the data pipelines and models that underpin Fourth’s single source of truth. You will gather and translate business requirements into reliable, well-tested data solutions on our Azure-based cloud platform. You will collaborate closely with analytics engineers and business stakeholders to scope, prioritise, and deliver data products that serve FP&A, Commercial, Product, and AI teams. As Fourth moves towards an AI-native operating model, you will play a key role in building and maintaining the data infrastructure that enables AI-powered analytics and decision-making across the business.
Responsibilities:
Data Pipeline Development & Optimisation
- Build, maintain, and optimise scalable ETL/ELT pipelines (batch and near-real-time) on Azure Data Cloud Platform (e.g., Data Lake, Microsoft Fabric, Azure Data Factory).
- Develop and refine data models to support BI reporting, analytics, and ML/AI use cases.
- Write efficient, well-documented T-SQL and PySpark code following team coding standards.
- Implement automated testing, data validation, and monitoring (SLAs, alerts) to ensure pipeline reliability.
- Contribute to data governance practices, including lineage tracking, metadata management, and quality controls.
- Support CI/CD pipelines for data assets, ensuring version control and reproducibility.
- Partner with Analytics Engineers to scope, refine, and prioritise data requirements from business stakeholders.
- Work with Analysts, BI Developers, Data Scientists, and business teams to translate requirements into production-ready data solutions.
- Provide input on data readiness for machine learning and analytics projects.
- Contribute to the evolution of the data platform, including tooling, standards, and documentation.
- Stay current with emerging data engineering patterns and technologies; propose improvements to team processes.
- Use AI as an integral part of the development workflow: code generation, data profiling, testing, documentation, and task management.
- Contribute to building a data platform that is AI-ready: well-documented, semantically clear, and structured for reliable consumption by AI tools and agents.
- Support performance tuning and cost optimisation across the data platform.
- 3+ years in data engineering or a closely related role.
- Bachelor’s degree in Computer Science, Data Engineering, or a related field.
- Technical Skills:
○ Hands-on experience with MS Azure Storage Explorer and SSMS.
○ Hands-on experience with cloud-based data engineering services and orchestration tools (e.g., Azure Data Factory, Microsoft Fabric).
○ Practical experience building ETL/ELT pipelines and dimensional or analytical data models.
○ Familiarity with CI/CD practices in data engineering, including version control (Git) and automated testing.
○ Active use of AI productivity tools (e.g., ChatGPT, Claude, Copilot, Cursor) as an integrated part of development, testing, documentation, and day-to-day engineering workflows.
- Soft Skills:
○ Good documentation habits and a willingness to communicate technical concepts clearly.
○ Proactive and timely communication on progress, blockers, and dependencies with stakeholders and team members.
○ Strong analytical and problem-solving mindset.
○ Proactive, detail-oriented, and comfortable working in an agile, fast-paced environment.
○ Proficiency in English, both spoken and written.
Preferred Qualifications:
- Experience with real-time or streaming data architectures.
- Experience with PowerShell, Apache Kafka, and/or KQL.
- Exposure to AI/ML workflows (feature engineering, data preparation for model training).
- Familiarity with Power BI or other BI/visualisation tools.
- Understanding of data security, privacy, and compliance considerations.
- 25+ days off, as well as birthday day off and 4 charity days off per year
- Flexible start and end of the working day and hybrid working mode, including a combination remote and in the office
- Team-centric atmosphere
- Encouraging healthy lifestyle and work-life balance including supplemental health insurance
- New parents bonus scheme
- Only short-listed candidates will be contacted.
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