Senior Manager, Data Quality & Issue Management

Overview

Who we are

Who were looking for

Toyota Financial Services (TFS) Technology is seeking a highly motivated and strategic leader to serve as the Senior Manager Data Quality & Issue Management. In this role you will operate as a technology lead with deep expertise in Data Quality Issue Management and strong technical proficiency in data engineering. You will shape and drive the strategy vision and roadmap that elevate TFSs enterprise data landscape and ensure the delivery of trusted highvalue data across the organization.

As the Senior Manager Data Quality & Issue Management you will define and execute the enterprise data quality vision and roadmap embedding robust quality controls maturing issuemanagement processes and advancing data transparency usability and governance. Through your technical leadership you will guide teams in implementing scalable dataquality solutions enhancing data pipelines and aligning quality standards with TFSs enterprise data objectives.

You will lead and develop a highperforming team fostering a culture grounded in accountability continuous improvement and crossfunctional collaboration. Your leadership will ensure that TFSs data ecosystem is reliable wellgoverned and fully equipped to support critical business decisions meet regulatory expectations and drive longterm data product quality transformation across the enterprise.

What youll be doing

• Define and execute the enterprise dataquality strategy roadmap and operating model tailored to the needs of a captive autofinance business ensuring trusted accurate and timely data across lending servicing collections and risk functions.

• Lead and develop two highperforming teams a combined group of 20 dataquality analysts engineers stewards and business partners while fostering a culture of accountability continuous improvement and innovation.

• Oversee the enterprise Issue Management program with strong executive presence and clear influential communication to senior leadership. Set strategic direction remove barriers and elevate dataquality standards enterprisewide.

• Drive the enterprise Data Quality Issue Management program with strong executive presence ensuring clear concise and influential communication with senior leadership.

• Provide strategic direction remove obstacles and elevate dataquality standards across the organization through disciplined execution crossfunctional alignment and proactive risk management.

• Govern the endtoend issuemanagement process including detection triage rootcause analysis remediation planning and closure ensuring alignment with regulatory expectations and internal controls.

• Strengthen data governance practices by establishing standards policies and controls that improve data transparency lineage and accountability across business and technology teams.

• Design and operationalize automated dataquality rules monitoring and scorecards using tools such as Informatica CDGC/CDQ and Collibra ensuring consistent measurement of data accuracy completeness timeliness and validity.

• Collaborate closely with data engineering teams to embed quality checks into pipelines optimize data flows and ensure scalable resilient dataengineering solutions that support underwriting funding servicing and collections.

• Apply emerging Agentic AI and MCPbased automation to enhance dataquality detection anomaly identification issue triage and remediation workflows accelerating timetoresolution and reducing manual effort.

• Partner with business units (Originations Servicing Collections Risk Compliance Finance) to understand data needs resolve issues and ensure alignment with enterprise data objectives and regulatory requirements.

• Build mentor and develop a highperforming team of dataquality analysts engineers and stewards fostering a culture of accountability continuous improvement and innovation.

• Ensure dataquality and issuemanagement processes support regulatory compliance (e.g. fair lending credit reporting accuracy privacy model governance) and withstand audit and examination scrutiny.

• Partners with data product owners to embed quality standards into data products ensuring reliability usability and trustworthiness across analytics reporting and AI/ML use cases.

• Establish and track key dataquality KPIs KRI metrics dashboards and scorecards to measure performance identify trends and drive continuous improvement.

• Promote data literacy and stewardship across the organization enabling business teams to better understand data definitions lineage and quality expectations.

What you bring

• 10 - 12 years leading enterprise dataquality programs including strategy controls monitoring and remediation across complex financialservices environments

• Proven experience managing the full issue lifecycle (identification triage RCA remediation closure) with strong familiarity with regulatory expectations in lending and credit reporting

• Handson experience supporting data needs across originations customer servicing collections funding remarketing credit risk and compliance within a captive or consumerlending organization

• Experience partnering with data engineering teams to embed quality checks into pipelines optimize data flows and implement scalable dataquality solutions

• Practical experience implementing and operationalizing data cataloging lineage and dataquality rules using Informatica CDGC and CDQ

• Strong background in metadata management stewardship workflows and governance operating models using Collibra

• Experience using Jira and Confluence to manage issue workflows documentation governance processes and crossfunctional collaboration

• Exposure to or handson experience applying Agentic AI or MCPbased automation to enhance dataquality detection anomaly identification and issueremediation workflows

• Experience supporting regulatory requirements such as credit reporting accuracy fair lending model governance data privacy and audit readiness

• Deep understanding of governance frameworks data ownership models stewardship and enterprise datamanagement practices

• Demonstrated success leading and developing highperforming data teams fostering accountability continuous improvement and crossfunctional alignment

• Experience embedding quality standards into data products ensuring reliability for analytics reporting and AI/ML use cases

• Experience defining and tracking dataquality KPIs dashboards and scorecards to measure performance and drive improvement

Added bonus if you have

• Hands-on experience with data governance tools such as Collibra and Informatica CDGC/CDQ

• Proficiency in working with modern data engineering platforms including Snowflake Apache Iceberg and Databricks

• Strong understanding of data modeling concepts and best practices

• Advanced expertise in writing optimizing and interpreting complex SQL queries

• Experience in real-time data streaming platforms including Apache Kafka along with expertise in building and integrating RESTful microservices APIs

• Deep understanding of data products including lifecycle management and domain-driven design principles

• Knowledge of Agentic architecture and Model Context Protocols (MCPs) to enable proactive data quality monitoring and data observability

What well bring

During your interview process our team can fill you in on all the details of our industry-leading benefits and career development opportunities. A few highlights include:

• A work environment built on teamwork flexibility and respect

• Professional growth and development programs to help advance your career as well as tuition reimbursement

• Team Member Vehicle Purchase Discount

• Toyota Team Member Lease Vehicle Program (if applicable)

• Comprehensive health care and wellness plans for your entire family

• Toyota 401(k) Savings Plan featuring a company match as well as an annual retirement contribution from Toyota regardless of whether you contribute

• Paid holidays and paid time off

• Referral services related to prenatal services adoption childcare schools and more

• Tax Advantage Accounts (Health Savings Account Health Care FSA Dependent Care FSA

• Relocation assistance (if applicable)

Belonging at Toyota

Our success begins and ends with our people. We embrace all perspectives and value unique human experiences. Respect for all is our North Star. Toyota is proud to have 10 different Business Partnering Groups across 100 different North American chapter locations that support team members efforts to dream do and grow without questioning that they belong.

Applicants for our positions are considered without regard to race ethnicity national origin sex sexual orientation gender identity or expression age disability religion military or veteran status or any other characteristics protected by law.

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