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Data Engineer
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We are a Global Recruitment specialist that provides support to the clients across EMEA, APAC, US and Canada. We have an excellent job opportunity for you.
Job Title: Lead Data Engineer
Location: Remote
Duration: Until 31/03/2027
Pay Rate: £660 per day all inc. (PAYE through Umbrella)
Sector: Public
Clearance required: Needs to hold SC
Role Purpose
We are seeking two experienced Azure Data Engineers to accelerate delivery of the APHA Data Platform and implement the silver layer of our enterprise data architecture.
The successful candidates will design, build, automate and maintain scalable data engineering solutions supporting the Data Platform, Common Data Model (CDM), reporting, analytics, Master Data Management (MDM) and future AI capabilities.
This is a critical delivery role responsible for transforming data from multiple legacy and operational systems into trusted, governed and reusable data products that support decision-making across APHA.
The role is expected to be prioritised as a key dependency for Silver Layer implementation and Data Platform delivery.
Key Responsibilities
Data Platform Engineering
- Design, build and support Azure Data Platform solutions.
- Develop robust ingestion pipelines from operational and legacy systems.
- Build and maintain Bronze, Silver and Gold data layers.
- Implement scalable data lake and data warehouse structures.
- Develop reusable engineering patterns and framework components.
Silver Layer & Common Data Model Delivery
- Implement and maintain Silver Layer business data models.
- Translate logical and physical data models into deployable solutions.
- Develop SQL transformations required to map source systems into the Common Data Model.
- Support integration of data from multiple services and domains.
- Ensure consistency of mastered and governed data.
- Write LLDs (Low level design) documentation for Engineering development tasks.
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Data Pipeline Development
- Design, build and optimise ETL/ELT pipelines.
- Develop automated batch and near real-time ingestion solutions.
- Implement Change Data Capture (CDC) where appropriate.
- Automate data validation and exception handling.
- Build monitoring and alerting capabilities.
Platform Automation & DevOps
- Develop deployment automation.
- Implement CI/CD pipelines.
- Manage code repositories and version control.
- Support Infrastructure as Code approaches.
Data Quality & Governance
- Implement data quality controls.
- Support metadata and lineage capture.
- Work alongside governance and architecture teams.
- Ensure compliance with security and data protection requirements.
- Assist in operationalising governance standards.
Knowledge Management & Reusable Assets
- Create and maintain engineering standards.
- Produce technical documentation and runbooks.
- Build a reusable engineering knowledge bank.
- Create reusable templates, patterns and accelerators.
- Capture lessons learned from delivery activities.
- Support knowledge transfer to permanent APHA teams.
Technical Skills Required
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Essential
- Azure Data Factory
- Azure Databricks
- Azure SQL
- Python
- ETL / ELT development
- Data Lake architecture
- Data Warehousing
- Git
- Azure DevOps
- CI/CD pipelines
- Data Modelling
- Performance tuning
- REST API integration
Highly Desirable
- Microsoft Purview
- Semarchy MDM
- Event Hub
- Stream Analytics
- CDC implementations
- Master Data Management
- Power BI data modelling
Deliverables
Priority 1
- Silver Layer implementation
- Common Data Model engineering implementation
- Data ingestion framework
- Automated pipeline framework
Priority 2
- Gold layer implementation
- Monitoring and alerting framework
- Deployment automation
- Data quality controls
- Metadata and lineage integration
Priority 3
- Engineering Knowledge Bank
- Reusable templates and accelerators
- Technical runbooks
- Operational support documentation
- Handover and knowledge transfer materials
Knowledge Bank Responsibilities
The Data Engineers will:
- Document all architecture decisions and engineering patterns.
- Produce source-to-target mappings.
- Create pipeline design documentation.
- Maintain operational support guides.
- Record lessons learned and reusable assets.
- Support onboarding of future engineering resources.
If you are interested in this position and would like to learn more, please send through your CV and we will get in touch with you as soon as possible. Please note, candidates are often Shortlisted within 48 hours.
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