At Moniepoint, data serves as the foundation of our financial operating system.
The Senior Data Quality Analyst will define, measure, monitor, and elevate the quality of enterprise data assets.
Reporting directly to the Head of Data Governance, this role collaborates with Data Owners, Data Stewards, Data Engineering, and cross-functional business units to ensure data remains accurate, complete, consistent, timely, and fit for purpose.
Beyond managing technical frameworks, this position acts as a cultural catalyst for data accountabilityguiding a cross-functional network of Data Stewards across domains such as Finance and Sales to establish unified, enterprise-grade data management standards that protect and optimise data for over 13 million customers.
Responsibilities
Framework & Metrics Execution: Implement and maintain data quality rules, metrics, and thresholds across priority data domains.
Profiling & Root-Cause Analysis: Conduct comprehensive data profiling and quality assessments to identify anomalies, structural gaps, and underlying causes of degraded data quality.
Reporting & Governance Dashboards: Develop and maintain data quality scorecards and operational dashboards to report trends, risks, and health metrics to executive leadership and key stakeholders.
Standards & Remediation Collaboration: Partner with Data Owners and Stewards to define acceptance criteria for critical data elements (CDEs) and lead remediation initiatives for high-impact or recurring data issues.
Tooling & Architecture Integration: Configure and support enterprise data quality platforms (e.g., catalog integrations, automated monitoring) and collaborate with Data Engineering to embed quality checks directly into ETL/ELT pipelines.
Documentation & Compliance: Maintain data quality playbooks, rule libraries, and issue logs. Support internal/external audits and regulatory compliance reviews by presenting evidence of robust data quality controls.
Governance Advancement: Drive broader enterprise data governance initiatives, including metadata management, data lineage, data classification, and policy enforcement.
Experience & Background
Bachelor's degree in Data Management, Computer Science, Information Systems, Statistics, or a related quantitative field.
5+ years of experience in data quality, data governance, or advanced data analytics.
Prior experience within regulated sectors, specifically Financial Services, Fintech, Telecommunications, or Insurance.
Strong working knowledge of data privacy regulations, including NDPR, GDPR, and fintech compliance standards.
Solid foundation in core data governance principles, including data ownership, stewardship models, lineage, and data classification.
Deep familiarity with modern data architectures (Medallion, Data Mesh, Data Vault 2.0) and implementing governance within distributed environments.
Experience mentoring junior analysts or leading discrete governance workstreams.
Skills & Competencies:
Advanced SQL skills with extensive experience querying, profiling, and analysing complex, large-scale datasets.
High proficiency in Python/SQL for automating data quality checks, accessing APIs, and querying data platforms directly.
Practical experience with enterprise data governance and profiling platforms (e.g., Collibra, Microsoft Purview, Solidatus, Informatica DQ, DataHub).
Proven track record building data quality dashboards using tools such as Power BI, Apache Superset, Grafana, Metabase, or TIBCO.
Exceptional stakeholder management skills with a demonstrated ability to translate complex technical findings into actionable business insights.
What success looks like in this role
Data quality frameworks, metrics, and thresholds are successfully implemented and maintained across all priority data domains.
Data quality scorecards and operational dashboards provide executive leadership and key stakeholders with clear, actionable insights into data health and risks.
A strong culture of data accountability is established across cross-functional domains, empowering Data Stewards to uphold unified management standards.
High-impact data issues are effectively remediated, and robust quality controls are seamlessly embedded into ETL/ELT pipelines.
What we can offer you
Culture -We put our people first and prioritise the well-being of every team member. We've built a company where all opinions carry weight and where all voices are heard. We value and respect each other and always look out for one another. Above all, we are human.
Learning - We have a learning and development-focused environment with an emphasis on knowledge sharing, training, and regular internal technical talks.
Compensation - You'll receive an attractive salary, pension, health insurance, annual bonus, plus other benefits.
What to expect in the hiring process
A preliminary phone call with the recruiter
A technical interview with the Hiring Manager
A behavioural and technical interview with a member of the Executive team.