Data Quality Analyst

Join Mizuho as a Banking Domain Data Quality Analyst!

The Enterprise Data Management function is responsible for effective and consistent Data Management of the bank’s data which in deemed critical: Used in external reporting, used to continuously provide information to bank management, and data whose deficiency can cause financial loss/severe impact to the customer.

Mizuho’s data operating model is comprised of enterprise-wide groups and federated data domains to drive accountability and management of data. The federated operating model ensures minimal overlaps and reduced handoffs of data attributes across the data lifecycle. Federated data domains are defined according to the various types of data originated and consumed by the enterprise (transactional, derived, and master/reference), and in such manner that there are no unclaimed or overlapping data elements between two domains. Their definition and structure aim to support Mizuho’s business activities and operations. Data is clustered into federated domains with overall accountability and ownership for data quality, from origination to consumption.

Data Domains core responsibilities include definition and ownership of business use cases, serving as owners for and managing data within the domain (selected with view to exhaustively cover data within the enterprise with no overlaps), ensuring data satisfies the needs of data consumers, managing data quality assessments and remediation with source systems, expressing the data model and data definitions for the data elements within the domain, and participating in the enterprise data governance bodies.

Role Description:

In the context of the replacement of the current lending system (ACBS) to LoanIQ platform, the Banking Data Domain is looking for a LoanIQ DQ Analyst that will act as the lead to ensuring that the project meets data best practices, and that the outcome complies with Enterprise Data Management standards. Also needs strong analytical skills, ability to anticipate issues, verify the enhancements, and trouble shoot project execution issues. Must be adept at making data useful and digestible by all parties involved. Strong SQL scripting and analysis skills are required. 

Major Responsibilities:

As a Banking Domain Data Quality Analyst, you will be working directly with the Banking Data Steward, as the driving force behind our end-to-end data strategy. We are seeking a meticulous and analytical Banking Data Quality, Analytics, and Controls Analyst to join our management team. This role requires strong data management skills, proficiency in data analysis tools, and a deep understanding of data management practices.

• Work with business users to understand their needs and document them using various tools
  • Anticipate user needs and propose solutions and alternatives
  • Understand functional and non-functional requirements
• Work with project teams in building and testing the solutions
• Manage data requirements.  Able to prioritize and allocate resources effectively
• Quality control of LoanIQ
• Maintain active communication channels with all stakeholders on deliverables and report statuses
• Track all outstanding issues and manage them from initiation to production deployment
• Work closely with LoanIQ project team, Operations group, risk management, IT, and data governance teams to ensure data needs are met and risks are managed effectively.
• Proactively plan for robust and smooth transition from Project mode to Run-The-Bank (RTB) mode. Ultimately ensure knowledge and skillset are maintained withing the organization. Act as LoanIQ Data Subject Master Expert.
• Provide training and guidance to team members on data quality, analytics, and controls best practices.

Skills:

• Working knowledge of the financial industry is required.
• Working knowledge on migration or implementation of banking systems.
• Demonstrable proficiency with SQL Server and data mining skills, Python, Schema mapping.
• Familiarity with Data models and modeling.
• Excellent with MS Office tools (Words, Excel, PowerPoint, Visio).
• Working knowledge of JIRA and familiarity with Agile methodology.
• Strong knowledge and experience of regulatory change management.
• Strong experience in application support is preferred.
• Ability to multitask and work with multiple teams.
• Communicate complex data findings and risk insights to non-technical stakeholders in a clear and actionable manner.

Qualifications:

Education:

• Bachelor’s degree or equivalent work experience in Data Science, Statistics, Risk Management, Information Systems, or a related field.

Experience:

• 7+ years of