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Fourth

Data Engineer – Azure, MS Fabric, Data Factory, PySpark

Fourth

. Design, build, and maintain data pipelines and models underpinning Fourth’s single source of truth .

Posted 11/10/2026full-timeMacclesfield • United KingdomMid-LevelSeniorWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and maintaining data pipelines and models on Azure, with strong proficiency in T-SQL and PySpark for data processing. Capable of collaborating with cross-functional teams to deliver scalable ETL/ELT solutions and ensuring data governance and quality.

Highest-signal resume keywords
Data Pipeline DevelopmentT-SQL ProficiencyAzure Data FactoryETL/ELT Pipeline OptimizationAI/ML Workflow Exposure

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
T-SQLPySparkETL/ELT PipelinesData ModelingData GovernanceAutomated TestingData ValidationPerformance TuningCI/CD PracticesData Profiling
Soft Skills
Analytical MindsetProactive CommunicationCollaborationProblem-SolvingDetail-Oriented
Tools & Technologies
Azure Data Cloud PlatformMS Azure Storage ExplorerSSMSMicrosoft FabricAzure Data FactoryPower BIGitAI Productivity Tools
Certifications & Qualifications
Bachelor’s Degree in Computer ScienceBachelor’s Degree in Data Engineering
Industry Keywords
Data EngineeringBusiness IntelligenceMachine LearningData SecurityData PrivacyCompliance

Tech Stack

Tools & technologies
ApacheAzureCloudETLKafkaPySparkPythonSQL

About the role

Key responsibilities & impact
  • Design, build, and maintain data pipelines and models underpinning Fourth’s single source of truth
  • Gather and translate business requirements into reliable, well-tested data solutions on the Azure-based cloud platform
  • Collaborate with analytics engineers and business stakeholders to scope, prioritise, and deliver data products for FP&A, Commercial, Product, and AI teams
  • Build, maintain, and optimise scalable batch and near-real-time ETL/ELT pipelines on Azure Data Cloud Platform
  • Develop and refine data models for BI reporting, analytics, and ML/AI use cases
  • Write efficient, well-documented T-SQL and PySpark code
  • Implement automated testing, data validation, monitoring, SLAs, and alerts
  • Contribute to data governance, lineage tracking, metadata management, and quality controls
  • Support CI/CD pipelines for data assets, version control, and reproducibility
  • Partner with Analytics Engineers to scope, refine, and prioritise data requirements
  • Work with Analysts, BI Developers, Data Scientists, and business teams to create 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 data engineering patterns and technologies and propose process improvements
  • Use AI for code generation, data profiling, testing, documentation, and task management
  • Build an AI-ready data platform that is well-documented, semantically clear, and structured for reliable consumption by AI tools and agents
  • Support performance tuning and cost optimisation across the data platform

Requirements

What you’ll need
  • 3+ years in data engineering or a closely related role
  • Bachelor’s degree in Computer Science, Data Engineering, or a related field
  • Strong T-SQL skills
  • Working proficiency in PySpark or Python for data processing
  • Hands-on experience with MS Azure Storage Explorer and SSMS
  • Hands-on experience with cloud-based data engineering services and orchestration tools, such as Azure Data Factory and Microsoft Fabric
  • Practical experience building ETL/ELT pipelines and dimensional or analytical data models
  • Familiarity with CI/CD practices in data engineering, including Git and automated testing
  • Active use of AI productivity tools such as ChatGPT, Claude, Copilot, or Cursor in development, testing, documentation, and engineering workflows
  • Ability to work collaboratively with technical and non-technical stakeholders
  • Good documentation habits and ability to communicate technical concepts clearly
  • Proactive and timely communication regarding progress, blockers, and dependencies
  • Strong analytical and problem-solving mindset
  • Proactive, detail-oriented, and comfortable working in an agile, fast-paced environment
  • Proficiency in English, spoken and written
  • Preferred: experience with real-time or streaming data architectures
  • Preferred: experience with PowerShell, Apache Kafka, and/or KQL
  • Preferred: exposure to AI/ML workflows
  • Preferred: familiarity with Power BI or other BI/visualisation tools
  • Preferred: understanding of data security, privacy, and compliance considerations

Benefits

Comp & perks
  • 25 basic holidays, with the option to grow up to 30 with service
  • Birthday off
  • Bank holidays
  • Flexible working hours
  • Hybrid working environment
  • Wellness activities
  • Gym subscription discounts
  • Laptop and equipment
  • Healthcare expense claim tools
  • Certifications and professional growth opportunities
  • Annual meet-ups
  • Enhanced parenting scheme
  • Cycle to work scheme
  • Season ticket loan
  • Pension options
  • Life insurance options
  • On-demand pay tools