We’re looking for a motivated, analytical and solutions-focused Data Quality Developer who is passionate about using technology and high-quality data to drive better decisions and improve services. At Southern Housing, we believe reliable data and meaningful insight are essential to supporting our residents and shaping the future of our organisation, and this role will play a vital part in making that happen.
Reporting to the Head of Data Quality and Improvement, you’ll be the technical specialist responsible for designing, building, implementing and continuously improving our data quality solutions across Microsoft Fabric and Experian Aperture Data Studio.
You’ll focus on data quality development and engineering, creating reliable, controlled and traceable data flows between Microsoft Fabric and Aperture Data Studio. This will include developing the processes needed to profile, validate, cleanse and improve data, before returning approved outputs safely to Microsoft Fabric.
Working closely with the Data Quality and Improvement Manager, Data Engineers and the Data Engineering Guild, you’ll translate data quality requirements into scalable, secure and supportable technical solutions. You’ll also help ensure that the required data, metadata and technical information are available to support effective profiling, rule development, monitoring and continuous improvement.
You’ll design, build and maintain data quality pipelines, transformations and supporting processes, while configuring and developing data quality tooling within Aperture Data Studio. This may include connections, datasets, profiling, validation, standardisation, cleansing, matching, transformation and export processes.
You’ll also support the design and implementation of ETL and ELT processes, data models and integration patterns. Where possible, you’ll automate data quality monitoring and processing, supported by appropriate controls, logging, documentation and exception handling.
As part of the role, you’ll investigate and resolve technical data quality issues across Microsoft Fabric, Aperture Data Studio and connected data flows. You’ll monitor the performance, reliability and completeness of data quality processes and ensure that solutions comply with our data governance, information security, data protection, architecture and change-control requirements.
This role is based at our Farringdon office, with the option to work in a hybrid way where appropriate and as agreed with your manager.
If you’re curious, detail-oriented and enjoy solving complex technical and data challenges, you’ll fit right in. You’ll be confident turning data quality requirements into dependable technical solutions and comfortable working collaboratively with both technical specialists and data quality practitioners.
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Strong practical experience of Microsoft Fabric, including data engineering workloads, Lakehouse or Warehouse structures, notebooks, pipelines and medallion architecture
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Strong practical experience of SQL and at least one relevant programming language, such as Python, Postgres, PySpark or Java
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A strong understanding of data quality principles and processes, including data profiling, validation, standardisation, cleansing, matching, monitoring and exception management
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An understanding of database design, data modelling, metadata, data lineage, version control, testing and deployment practices
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Experience working with relevant Microsoft data technologies, which may include Microsoft Azure data services, Azure Data Factory, Azure Analysis Services, Microsoft SQL Server, Power BI, data lakes and data management tools.
You’ll be part of our Data Quality and Improvement team within the wider Data and Digital directorate, working alongside Data Quality Analysts, Data Engineers, developers, architects and other technical specialists
The team works collaboratively to improve the quality, reliability and usability of data across Southern Housing. This includes developing and maintaining data quality solutions, building controlled data flows, supporting data profiling and improvement activity, and ensuring that data can be used confidently to support operational and strategic decision-making.