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# Data Engineer

- **Company:** MaPS
- **Location:** Bedford, UK (Remote available)
- **Salary:** £53,000.0
- **Contract:** Permanent contract
- **Skills:** Clean Code Principles, Agile Methodology, Amazon Web Services, Architectural Patterns, Microsoft Azure, Cloud Computing, Cloud Database, Data Architecture, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Systems, Python (Programming Language), Power BI, Software Tools, SQL Databases, Data Streaming, Technical Data Management Systems, Data Storage Management, Azure Data Factory, Apache Spark, Microsoft Fabric, Data Lakes, Pyspark, Operational Systems, Data Management, Azure Synapse Analytics, Data Pipelines
- **Published:** September 21, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=6816c2398268ba1b

## About the Role

* Data Engineering experience, able to work independently following established patterns.
 * Experience implementing ETL processes ideally in an Azure/MS Fabric environment.
 * Experience and genuine competence in using SQL to query and manipulate data.
 * Proficiency in cloud data tooling such as Synapse Analytics, Microsoft Fabric, Azure Data Factory or AWS equivalents.
 * Spark/Pyspark or Python skills.
 * Excellent problem-solving skills and attention to detail.
 * Strong communication and collaboration skills.
 * MS Fabric interest, skills or experience a bonus.
 * Willingness to learn and a genuine enthusiasm for cloud technology and data.

## Description

Join us at the Money and Pensions Service (MaPS) as a Data Engineer where you will design and implement data pipelines to connect operational systems, engineering data for analytics and business intelligence (BI) systems in a cloud-only environment, predominantly Microsoft Fabric on Azure.

This role offers the opportunity to work with Senior Engineers on cloud-based data engineering pipelines and be part of developing our technical data architecture and platform.

We're especially interested in candidates who can show how their technical work has solved real business problems or improved outcomes for users, not just a list of technical skills.

The Data Engineer reports to the Senior Data Engineer. The role is aligned to the Government Digital and Data Profession Capability Framework: Data Engineer: https://ddat-capability-framework.service.gov.uk/role/data-engineer#data-engineer

You'll be part of a dynamic team dedicated to helping people across the UK improve their financial wellbeing.

Key Responsibilities:

Data Pipelines and ETL Processes

 * ETL Implementation: Implement ETL processes within MaPS architectural patterns to extract, transform, and load data from various source systems into our reporting solutions.

 * Pipeline Development: Develop and configure meta-data driven data pipelines using data orchestration tools such as Azure Data factory and engineering tools like Apache Spark to ensure seamless data flow.

 * Monitoring and Failure Recovery: Implement monitoring procedures to detect failures or unusual data profiles and establish recovery processes to maintain data integrity.

Azure Services

 * Utilise Cloud based data technology platforms, Data Lake based storage & Cloud data pipeline/orchestration tools for efficient data storage, processing, and transfer.

 * Ensure the scalability and reliability of data solutions using Azure's suite of services.

Collaboration

 * Work closely with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions that meet their needs.

 * Working within Agile methodology, helping to build clear user stories and work items.

Data Governance and Quality

 * Ensure data governance policies are adhered to and maintain high standards of data quality and security.

 * Develop pipelines using best practices for data management and integration.

 * Ensure only thoroughly tested, high-quality code and resulting Data Products are delivered to the MaPS business.

Data Landscape

 * Broad understanding & interest of architectural principles underlying modern data architecture. E.g. Data Lakes, External tables, medallion architecture, loose coupling.

 * Reporting & analysis tooling. A high-level understanding of report tooling such as Power BI & the needs of analysts consuming engineered data into these tools.