Finance Domain Data Quality Analyst

Mizuho Financial group•New York, NY

62d•$77,000 - $135,000•Hybrid

About The Position

As a Finance Domain Data Quality Analyst, you will be working directly with the Finance Data Steward, as the driving force behind our end-to-end data strategy, acting as the subject matter expert in the Finance Data domain, supporting the Domain Sponsor, Data Consumers, Data Owners as well as Data Architects. The primary function of the Data Stewards & Data Quality Analysts is to ensure the data assets of their domain are fit-for-use (analytical or operational) and fit -for-purpose. Fluent in data concepts, governance, and quality, you will collaborate closely with business teams, IT leads, and data consumers to create and execute a comprehensive data strategy. You will spend a significant amount of time directly engaging with business contacts to understand data requirements, data model and architecture, usage, and challenges to be addressed by the data strategy. We are seeking a meticulous and analytical Finance Data Quality, Analytics, and Controls Analyst to join our management team. The successful candidate will be responsible for ensuring the quality and integrity of finance-related data, investigating authoritative sourcing of data, conducting data analysis to support risk assessments, and implementing data control measures to safeguard critical data assets. This role requires strong data management skills, proficiency in data analysis tools, and a deep understanding of data management practices.

Requirements

Bachelor's degree or equivalent work experience in Data Science, Statistics, Risk Management, Information Systems, or a related field.
3+ years of experience in data quality management, data analytics, or risk management.
Proven experience in implementing data controls and governance frameworks.
Proficiency in SQL, Excel, and data analytics tools (e.g., SAS, Python).
Experience with data design, data audit, data governance, visualization tools (e.g. Power BI). Experience with business and IT stakeholders.
Strong analytical and problem-solving skills.
Excellent attention to detail and organizational abilities.
Knowledge of data sources, transformation rules, and uses of data for the domain. Experience with Finance products, frameworks, and practices.
Demonstrated passion for stakeholder engagement and support.
Strong organizational/project management skills, attention to detail, interpersonal communication skills.
Ability to work independently and collaboratively in a fast-paced environment.

Responsibilities

Develop and maintain data catalog, list of pain points, dashboards, reports, and visualizations to provide insights to stakeholders.
Drive data lineage to ensure sourcing from authorized systems
Maintain and identify changes needed in metadata for domain data.
Analyze large datasets to identify trends, patterns, and risk factors that may impact the organization.
Perform ad-hoc analysis to answer specific needs.
Develop and manage data quality controls for domain to ensure the accuracy, completeness, and consistency of data and identify trends and risk factors that may impact stakeholders and the organization.
Develop and maintain reporting to provide insights to stakeholders and identify / correct data discrepancies or anomalies.
Collaborate with data owners and IT teams to establish data quality standards and metrics.
Maintain documentation of data quality issues and corrective actions taken.
Develop and manage data quality controls to satisfy consumer's requirements.
Oversee remediation of Data Controls, including participating in root cause analyses, review & challenge of prioritization, criticality, and remedial actions. Participate in audits of data control processes as needed.
Perform data quality checks and audits to identify and rectify data discrepancies or anomalies.
Collaborate with data owners and IT teams to establish data quality standards and metrics.
Coordinate with the Data Quality Team to maintain documentation of data quality issues / corrective actions.
Work closely with risk management, compliance, IT, and data governance teams to ensure data needs are met and risks are managed effectively.
Communicate complex data findings and risk insights to non-technical stakeholders in a clear and actionable manner.
Provide training and guidance to team members on data quality, analytics, and controls best practices.