PENNYMAC Pennymac is (NYSE: PFSI) is a specialty financial services firm with a comprehensive mortgage platform and integrated business focused on the production and servicing of U.S. mortgage loans and the management of investments related to the U.S. mortgage market. At Pennymac, our people are the foundation of our success and at the heart of our dynamic work culture. Together, we work towards a unified goal of helping millions of Americans achieve aspirations of homeownership through the complete mortgage journey. A Typical Day This role leads the Production Finance data platform that designs, builds, and operates enterprise Data Mart / Hub structures used to measure operational and regulatory risk, support decision-making, and enable downstream reporting and analytics. Owns the end-to-end lifecycle of trusted production data: ingestion and transformation standards, platform migration and modernization (legacy SQL Server → Snowflake), data quality and validation, field-level logic/lineage, and partner delivery of contractual and corporate data commitments. Champions modern engineering practices, including AI-assisted development with Cursor, to accelerate delivery while preserving accuracy, governance, and production controls. Partners with IT, operations, finance, and investor/business stakeholders to ensure data is accurate, timely, well-governed, and fit for use — without owning the downstream BI/reporting layer itself. The First Vice President, Data & Analytics will: Data Mart / Hub Platform Leadership Own strategy and delivery for Production Finance Data Mart / Hub assets (tables, stored procedures, pipelines) that store and transform enterprise information into definitive, consumption-ready structures. Set engineering standards for sequential, high-performance SQL (legacy T-SQL and Snowflake SQL), deployment discipline, and operational reliability. Partner with IT on storage, transformation, security, and change-control protocols across on-prem SQL Server and Snowflake. Drive modernization of legacy SQL Server data platforms to Snowflake, with zero-tolerance standards for timing, syntax, and data-type mismatches during cutover. AI-Enabled Engineering (Cursor) Establish and scale team standards for AI-assisted development using Cursor (and related AI coding tools) for SQL authoring, migration, validation, lineage analysis, and operational triage. Define guardrails so AI acceleration does not compromise data correctness, security, change control, or production deploy discipline. Coach engineers on effective human-in-the-loop use of Cursor: prompt discipline, review of AI-generated SQL/scripts, and accountability for outcomes. Continuously evaluate opportunities to improve throughput and consistency through AI-augmented workflows without shifting ownership of production decisions away from the team. Data Quality, Validation & Governance Lead the Data Governance framework for the division: identify, design, implement, and support data quality improvement initiatives using manual and automated controls. Establish continuous monitoring to detect, correct, and prevent invalid data; own issue tracking, remediation with business and IT partners, and quality metrics tied to organizational standards. Direct validation and triage practices (schema alignment, completeness, cell-level reconciliation) so production hubs remain trusted sources for risk, ops, and finance outcomes. Ensure field-level business logic and lineage are documented and explainable to downstream consumers and control partners. Analytics Enablement & Executive Insight (not report ownership) Enable Executive Reporting and Analytics by ensuring hubs, metrics definitions, and data contracts support Monthly Executive Management Reporting, business reviews, and recurring daily/weekly/monthly management metrics. Provide leadership and prioritization so operations and finance leaders receive accurate, timely data for planning, efficiency, controls, and client experience — coordinating with reporting/analytics partners rather than building dashboards or presentation layers as the team’s core product. Evaluate and implement strategies for using data and metrics to predict, improve, and measure fundamental risks to the division/operation. Operational Modeling & Capacity Support Oversee development of operational capacity and forecast inputs (volumes, staffing drivers, etc.) insofar as they depend on hub data products, metric definitions, and reliable historical/current-state data. Corporate Initiatives, Controls & External Commitments Lead delivery of key corporate and financially material data initiatives affecting Production Finance. Manage oversight of Investor and Business Partner contractual obligations related to data and reporting delivery (definitions, timeliness, reconciliation, change management). Align internal and external parties on data handoffs and process integrity for financially impacting workflows that depend on hub outputs. Perform other related duties as required and assigned. Demonstrate behaviors aligned with the organization’s desired culture and values. What You’ll Bring Deep expertise in SQL against large production datasets; strong comfort with both traditional RDBMS (e.g., SQL Server / T-SQL) and Snowflake. Proven experience owning or leading enterprise data mart / hub / warehouse engineering (ETL/ELT, stored procedures, pipeline reliability) — not solely report development. Experience adopting and leading teams in AI-assisted engineering workflows (Cursor preferred); able to raise productivity while enforcing rigorous review of AI-generated code and SQL. Strong understanding of financial and operational drivers in financial services; mortgage banking / servicing / production finance experience strongly preferred. Hands-on fluency with data quality, reconciliation, and validation methods at scale (completeness, accuracy, schema/contract drift). Experience with platform migration and dual-running environments (legacy SQL Server + Snowflake), including timing windows, type alignment, and cutover risk management. Familiarity with CI/CD for data (e.g., Git-based change management, Liquibase or equivalent) and structured collaboration with IT release processes. Ability to decode and communicate field-level business logic and lineage to executives, auditors, and downstream analytics consumers. Strong project leadership: prioritize multiple concurrent initiatives in a dynamic production environment. Self-directed; operates with urgency and accountability in a fast-paced business setting. Excellent critical thinking, problem solving, quantitative judgment, and executive-ready verbal/written communication. Proficient with Excel and presentation tools for stakeholder communication; advanced spreadsheet work is supporting, not the core craft. Track record of delivering timely, accurate information under operational pressure. Strong business acumen and ability to interface with executive management, IT, and control partners. Team builder with high attention to detail; able to lead engineers while remaining technically credible. WHAT SUCCESS LOOKS LIKE Production hubs are the trusted source of truth for division risk and performance metrics. Migrations and changes ship with measurable zero-defect (or rapidly remediated) validation outcomes. Governance and quality issues are visible, owned, and closed with clear metrics. Downstream reporting and ops partners can explain “why this field is what it is” without tribal knowledge. Contractual and corporate data commitments are met on time with auditable controls. The team consistently uses Cursor / AI-assisted workflows to move faster without sacrificing accuracy, auditability, or production control. Why You Should Join As one of the top mortgage lenders in the country, Pennymac has helped over 4 million lifetime homeowners achieve and sustain their aspirations of home. Our vision is to be the most trusted partner for home. Together, 4,000 Pennymac team members across the country are guided by our core values: to be Accountable, Reliable and Ethical in all that we do. Pennymac is committed to conducting a business that makes positive contributions and promotes long-term sustainable growth and to fostering an equitable and inclusive environment, where all employees and customers feel valued, respected and supported. Benefits That Bring It Home: Whether you're looking for flexible benefits for today, setting up short-term goals for tomorrow, or planning for long-term success and retirement, Pennymac's benefits have you covered. Some key benefits include: Comprehensive Medical, Dental, and Vision Paid Time Off Programs including vacation, holidays, illness, and parental leave Wellness Programs, Employee Recognition Programs, and onsite gyms and cafe style dining (select locations) Retirement benefits, life insurance, 401k match, and tuition reimbursement Philanthropy Programs including matching gifts, volunteer grants, charitable grants and corporate sponsorships We value the hard work and dedication of our employees. In addition to a competitive salary, positions may offer bonus opportunities. To learn more about our benefits visit: https://pennymacnews.page.link/benefits For residents with state required benefit information, additional information can be found at: https://www.pennymac.com/additional-benefits-information Compensation: Individual salary may vary based on multiple factors including specific role, geographic location / market data, and skills and experience as defined below: Lower in range - Building skills and experience in the role Mid-range - Experience and skills align with proficiency in the role Higher in range - Experience and skills add value above typical requirements of the role Some roles may be eligible for performance-based compensation and/or stock-based incentives awarded to employees based on company and individual performance. Salary $110,000 - $170,000 Work Model OFFICE This role leads the Production Finance data platform that designs, builds, and operates enterprise Data Mart / Hub structures used to measure operational and regulatory risk, support decision-making, and enable downstream reporting and analytics. Owns the end-to-end lifecycle of trusted production data: ingestion and transformation standards, platform migration and modernization (legacy SQL Server → Snowflake), data quality and validation, field-level logic/lineage, and partner delivery of contractual and corporate data commitments. Champions modern engineering practices, including AI-assisted development with Cursor, to accelerate delivery while preserving accuracy, governance, and production controls. Partners with IT, operations, finance, and investor/business stakeholders to ensure data is accurate, timely, well-governed, and fit for use — without owning the downstream BI/reporting layer itself. The First Vice President, Data & Analytics will: Data Mart / Hub Platform Leadership Own strategy and delivery for Production Finance Data Mart / Hub assets (tables, stored procedures, pipelines) that store and transform enterprise information into definitive, consumption-ready structures. Set engineering standards for sequential, high-performance SQL (legacy T-SQL and Snowflake SQL), deployment discipline, and operational reliability. Partner with IT on storage, transformation, security, and change-control protocols across on-prem SQL Server and Snowflake. Drive modernization of legacy SQL Server data platforms to Snowflake, with zero-tolerance standards for timing, syntax, and data-type mismatches during cutover. AI-Enabled Engineering (Cursor) Establish and scale team standards for AI-assisted development using Cursor (and related AI coding tools) for SQL authoring, migration, validation, lineage analysis, and operational triage. Define guardrails so AI acceleration does not compromise data correctness, security, change control, or production deploy discipline. Coach engineers on effective human-in-the-loop use of Cursor: prompt discipline, review of AI-generated SQL/scripts, and accountability for outcomes. Continuously evaluate opportunities to improve throughput and consistency through AI-augmented workflows without shifting ownership of production decisions away from the team. Data Quality, Validation & Governance Lead the Data Governance framework for the division: identify, design, implement, and support data quality improvement initiatives using manual and automated controls. Establish continuous monitoring to detect, correct, and prevent invalid data; own issue tracking, remediation with business and IT partners, and quality metrics tied to organizational standards. Direct validation and triage practices (schema alignment, completeness, cell-level reconciliation) so production hubs remain trusted sources for risk, ops, and finance outcomes. Ensure field-level business logic and lineage are documented and explainable to downstream consumers and control partners. Analytics Enablement & Executive Insight (not report ownership) Enable Executive Reporting and Analytics by ensuring hubs, metrics definitions, and data contracts support Monthly Executive Management Reporting, business reviews, and recurring daily/weekly/monthly management metrics. Provide leadership and prioritization so operations and finance leaders receive accurate, timely data for planning, efficiency, controls, and client experience — coordinating with reporting/analytics partners rather than building dashboards or presentation layers as the team’s core product. Evaluate and implement strategies for using data and metrics to predict, improve, and measure fundamental risks to the division/operation. Operational Modeling & Capacity Support Oversee development of operational capacity and forecast inputs (volumes, staffing drivers, etc.) insofar as they depend on hub data products, metric definitions, and reliable historical/current-state data. Corporate Initiatives, Controls & External Commitments Lead delivery of key corporate and financially material data initiatives affecting Production Finance. Manage oversight of Investor and Business Partner contractual obligations related to data and reporting delivery (definitions, timeliness, reconciliation, change management). Align internal and external parties on data handoffs and process integrity for financially impacting workflows that depend on hub outputs. Perform other related duties as required and assigned. Demonstrate behaviors aligned with the organization’s desired culture and values. Deep expertise in SQL against large production datasets; strong comfort with both traditional RDBMS (e.g., SQL Server / T-SQL) and Snowflake. Proven experience owning or leading enterprise data mart / hub / warehouse engineering (ETL/ELT, stored procedures, pipeline reliability) — not solely report development. Experience adopting and leading teams in AI-assisted engineering workflows (Cursor preferred); able to raise productivity while enforcing rigorous review of AI-generated code and SQL. Strong understanding of financial and operational drivers in financial services; mortgage banking / servicing / production finance experience strongly preferred. Hands-on fluency with data quality, reconciliation, and validation methods at scale (completeness, accuracy, schema/contract drift). Experience with platform migration and dual-running environments (legacy SQL Server + Snowflake), including timing windows, type alignment, and cutover risk management. Familiarity with CI/CD for data (e.g., Git-based change management, Liquibase or equivalent) and structured collaboration with IT release processes. Ability to decode and communicate field-level business logic and lineage to executives, auditors, and downstream analytics consumers. Strong project leadership: prioritize multiple concurrent initiatives in a dynamic production environment. Self-directed; operates with urgency and accountability in a fast-paced business setting. Excellent critical thinking, problem solving, quantitative judgment, and executive-ready verbal/written communication. Proficient with Excel and presentation tools for stakeholder communication; advanced spreadsheet work is supporting, not the core craft. Track record of delivering timely, accurate information under operational pressure. Strong business acumen and ability to interface with executive management, IT, and control partners. Team builder with high attention to detail; able to lead engineers while remaining technically credible. WHAT SUCCESS LOOKS LIKE Production hubs are the trusted source of truth for division risk and performance metrics. Migrations and changes ship with measurable zero-defect (or rapidly remediated) validation outcomes. Governance and quality issues are visible, owned, and closed with clear metrics. Downstream reporting and ops partners can explain “why this field is what it is” without tribal knowledge. Contractual and corporate data commitments are met on time with auditable controls. The team consistently uses Cursor / AI-assisted workflows to move faster without sacrificing accuracy, auditability, or production control.
