Data Quality Lead

Arrow Global Group; Manchester; On-site; GBP 65,000 - 90,000; Full time

Job summary

Arrow Global Group is seeking a Data Quality Lead in Manchester to define data quality standards and partner with IT to implement checks, dashboards, and alerts. You will drive continuous improvement and establish trust in data across asset management datasets including real estate, lending, and credit.

The role requires governance experience, strong stakeholder engagement, and a background in financial data domains.

Qualifications

• Degree in Computer Science, Information Systems, Data Science, or a related field.
• Demonstrated experience in a Data Governance or Data Management program.
• Proven experience leading data quality, data governance, or data controls in a data-rich environment (financial services, credit, real estate, asset management, or similar).
• A background in financial data domains (IBOR/ABOR, transactions, market data, reference data).
• Experience working with business stakeholders to define critical data elements, data definitions, and “fit for use” requirements.
• Familiarity with data quality tooling and modern orchestration/observability practices.
• Comfortable building processes from scratch in a newly formed team.
• Resourceful, motivated self-starter with the ability to collaborate across business and technology.
• Strong analytical, verbal, and written communication skills.

Responsibilities

• Establish domain-specific data quality rules and thresholds for core datasets across Real Estate, Lending & Credit.
• Define metrics to assess data quality performance and drive continuous improvement.
• Partner with Data Engineering to design automated checks, dashboards, and alerts for pipelines and reports.
• Lead root-cause analysis of data incidents and coordinate fixes with source platforms.
• Use trend analysis to prioritise remediation and improve data reliability and trust.
• Maintain expertise in data quality industry trends and implement advanced methodologies.

Skills

Data governance

Data quality tooling

Stakeholder engagement

Financial data domains

Instrumentation

Process improvement

Communication

Education

Degree in Computer Science / Information Systems / Data Science

Job description

Description

We are seeking a highly skilled and experienced Data Quality Lead (DQL) to fill a foundational role in a newly formed group concentrating on Data. This role will work closely with the business and Data Stewards to define what ‘good’ data looks like. The DQL also partners with Data Engineering to implement frameworks that ensure data quality aligns to business standards. Ultimately, this is a key position that will drive a continuous improvement process that builds trust and confidence in our data.

Department: IT & Change

Location: Manchester, UK

About The Role

• Establish domain specific data quality rules and dimension thresholds (accuracy, completeness, consistency, validity, timeliness) for core Asset Management datasets spanning Real Estate, Lending & Credit.


• Define and establish metrics to assess data quality performance and drive continuous improvement.


• Partner with Data Engineering to design automated checks, dashboards, and alerts for pipelines, data products, and key reports.


• Proactively lead root-cause analysis of data incidents. Coordinate fixes with source platforms.


• Use trend analysis to prioritize remediation, reduce chronic/recurring defects, and improve overall data reliability and trust.


• Maintain expertise in data quality industry trends and strategically implement advanced methodologies to elevate data quality practices.

About You

• Degree in Computer Science, Information Systems, Data Science, or a related field


• Demonstrated experience in a Data Governance or Data Management program


• Proven experience leading data quality, data governance, or data controls in a data rich environment (financial services, credit, real estate, asset management, or similar).


• A background in financial data domains (IBOR/ABOR, transactions, market data, reference data)


• Experience working with business stakeholders to define critical data elements, data definitions, and “fit for use” requirements.


• Familiarity with data quality tooling and modern orchestration/observability practices.


• Comfortable building processes from scratch in a newly formed team.


• Resourceful, motivated self-starter with the ability to collaborate across business and technology


• Strong analytical, verbal, and written communication skills