Job Title: Asset Data Quality Lead
Contract Type: Permanent
Salary: £38,897 (£42,992 is achieved after 12 months successful performance in the role)
Working Hours: 35 hours per week
Working Pattern: Monday - Friday
Location: Liverpool - National / Hybrid
Please note: this is not a BI analyst, data governance analyst, or data engineering role. The role sits within the operational asset management team and the post-holder will be expected to act as the operational subject matter expert for data relating to the composition and condition of housing assets, with a particular focus on component data collected on stock condition surveys and other technical inspections
The difference you will make as Asset Data Quality Lead
The Asset Data Quality Lead will lead on sourcing, assessing, monitoring, and improving the quality of asset data held within structured systems and databases. The role focuses on ensuring asset data from internal and external sources is complete, accurate, consistent, traceable, and fit for use across asset, compliance, investment, and operational decision-making, while ensuring opportunities to collect, improve, or enrich asset data are identified and exploited. The role provides assurance on the quality of asset data entering core systems, reports quality issues and trends, supports reconciliation across multiple data sources, and ensures corrective actions are completed to strengthen confidence in asset information.
About you
We are looking for someone with:
- Experience of working with stock condition data within social housing, or a similar built asset-focused environment.
- Experience of data validation, quality assurance, cleansing, reconciliation, or exception management within structured systems or databases.
- Ability to review and interpret asset records and related source data, including property, block, component, compliance, investment, lifecycle, or attribute information.
- Ability to analyse datasets, cross-reference internal and external data sources, and identify gaps, inconsistencies, errors, and trends.
- Experience of sourcing, reviewing, or supporting the quality assurance of data received from internal teams, external providers, contractors, surveyors, or third-party sources.
Why Riverside?
At Riverside, we’re a housing association with a difference – enhancing the everyday for all our customers. For 90 years, we’ve been revitalising neighbourhoods and supporting communities by providing the homes they need to live full, fulfilling and rewarding lives.
We have a portfolio of over 75,000 affordable residential and retirement homes across the UK. Our work ranges from homelessness services to social care, employment support to retirement living, and we need the best people on board to help us.
Working with us, you’ll enjoy:
- Competitive pay & generous pension
- 28 days holidays plus bank holidays
- Flexible working options available
- Investment in your learning, personal development and technology
- A wide range of benefits
Diversity and Inclusion at Riverside:
We are inclusive. At Riverside, we value diversity in all its forms. We foster a workplace where all individuals are respected, empowered, and heard. Our commitment to inclusivity drives our success and enriches the lives of our customers and colleagues.
This role also falls under our Ethnic Diversity guaranteedinterview scheme. If you are Ethnically Diverse and demonstrateyou meet the minimum criteriafor the role you will be guaranteed an interview.
Role Profile
The Asset Data Quality Lead will lead on sourcing, assessing, monitoring, and improving the quality of asset data held within structured systems and databases. The role focuses on ensuring asset data from internal and external sources is complete, accurate, consistent, traceable, and fit for use across asset, compliance, investment, and operational decision-making, while ensuring opportunities to collect, improve, or enrich asset data are identified and exploited. The role provides assurance on the quality of asset data entering core systems, reports quality issues and trends, supports reconciliation across multiple data sources, and ensures corrective actions are completed to strengthen confidence in asset information.
Asset Data Quality Assurance
- Lead on assessing the quality of asset data held within asset management systems, reporting datasets, and related data sources.
- Source asset data from internal teams, external providers, contractors, surveyors, and other relevant sources, ensuring it is suitable for loading, updating, or maintaining asset management systems.
- Manage the quality of asset data entering systems by applying validation checks, resolving exceptions, and confirming that incoming data meets agreed standards before or during system update processes.
- Ensure asset data collection opportunities are identified and exploited through surveys, inspections, works programmes, compliance activity, contractor engagement, and other operational touchpoints.
- Review and validate asset records including property, block, component, compliance, investment, lifecycle, and attribute data.
- Identify missing, duplicated, poor-quality, or inconsistent records, report findings clearly, and ensure issues are resolved.
- Assess whether asset data contains the information needed to support asset, compliance, investment, and operational decisions.
- Apply and use data standards to assess structure, traceability, and linkage to the correct asset, location, component, and source record.
Data Review and Reconciliation
- Compare asset data from internal and external sources against source records, survey outputs, compliance records, planned works, completed works, and historical datasets to identify discrepancies.
- Review incoming asset data before it is accepted into systems, ensuring required fields, coding, evidence, source references, and relationships between records are complete and consistent.
- Investigate inconsistencies, determine likely causes, and work with relevant teams and providers to ensure quality issues are resolved.
Stakeholder and Provider Liaison
- Provide formal feedback to internal teams, surveyors, contractors, and external providers on asset data quality issues, required improvements, and actions needed to resolve them.
- Clarify expectations for asset data capture, coding, evidence, source records, and submission standards to ensure consistency across teams and providers.
- Support onboarding and performance management of providers by reinforcing required quality standards for asset data outputs.
- Challenge recurring issues or significant failures where asset data does not meet agreed standards, elevate where required, and ensure corrective actions are completed.
Reporting and Performance Monitoring
- Produce reports on asset data quality performance, including issues relating to completeness, accuracy, consistency, timeliness, and traceability.
- Monitor trends such as inaccurate records, missing fields, inconsistent entries, weak source evidence, and recurring data issues.
- Highlight risks and fluctuations where poor-quality asset data could affect planning, compliance assurance, audit outcomes, reporting, or business decisions.
Process Improvement
- Develop and maintain quality assurance processes, standards, and guidance for asset data creation, maintenance, and correction.
- Recommend improvements to data templates, data capture tools, validation rules, and system controls to strengthen asset data quality.
- Identify opportunities to capture additional or improved asset data through existing processes, projects, visits, inspections, surveys, and provider activity.
- Contribute to continuous improvement by identifying root causes of recurring quality issues.
- Support the development of data dictionaries, validation frameworks, naming conventions, and asset data standards.
Success Measures
- Asset data from internal and external sources is consistently assessed, with quality issues clearly identified, reported, and resolved before or as it enters core systems.
- Internal teams and providers are challenged appropriately where data does not meet agreed standards.
- Data quality issues and trends are reported promptly, with clear escalation and timely completion of corrective actions where required.
- Data collection opportunities are proactively identified and used to improve the completeness, reliability, and value of asset data.
- Stakeholders have confidence in asset data used for investment planning, compliance reporting, operational delivery, and asset decision-making
Personal Specification
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