Quick overview
Job description
Data Architect – Mortgage & Capital Markets
The Data Architect – Mortgage & Capital Markets will be responsible for designing and implementing data architecture solutions for mortgage and capital markets. This role involves creating robust data models, ingestion pipelines, and data quality frameworks to support business workflows and analytics. The Data Architect will work closely with business stakeholders to translate their needs into scalable and efficient data solutions.
Responsibilities
- Own the end-to-end architecture of the Snowflake data warehouse, including account and database design, layered data modeling, security, and cost governance.
- Design data models for mortgage and capital markets domains, including loan-level servicing tapes, MSR portfolios, base and excess servicing, advances, remittances, prepayments, delinquencies, and trade and settlement data.
- Build ingestion pipelines from subservicers, trustees, custodians, valuation vendors, and internal systems, handling daily, monthly, and ad hoc file feeds (flat files, SFTP, APIs, Excel).
- Lead the transformation layer in dbt, covering model design, layered project structure, testing, documentation, CI/CD, and environment promotion.
- Implement data quality, reconciliation, and change-control frameworks, such as tape-to-tape comparisons, servicer-to-investor reconciliations, and month-end MSR workflow controls.
- Orchestrate pipelines using Snowpark, Streams/Tasks, Airflow, or Azure Data Factory alongside dbt.
- Design semantic and consumption-layer models in Snowflake that power Sigma workbooks for capital markets, portfolio analytics, finance, and operations users.
- Partner with business teams to build and govern Sigma dashboards and self-service analytics for MSR performance, servicing metrics, reconciliations, and investor reporting.
- Set up Sigma security aligned with Snowflake RBAC, including row-level security, user attributes, workspace governance, and the choice between OAuth and service-account connections.
- Enable Sigma input tables and write-back workflows where operations teams need to annotate, approve, or adjust data, such as reconciliation break resolution or month-end sign-offs.
- Design role-based access, masking policies for PII/NPI, row-level security, and audit logging to meet regulatory and investor requirements.
- Enable downstream consumption for Sigma, valuation, and risk models, and AI/LLM agents.
- Optimize warehouse sizing, clustering, query performance, and credit usage.
- Work directly with the client's capital markets, portfolio analytics, finance, and operations teams to translate business workflows into data architecture.
- Mentor data engineers and set coding, modeling, and documentation standards.
Requirements
<>Required Skills- 10+ years in data engineering or architecture, with 4+ years designing production Snowflake platforms.
- 3+ years of hands-on dbt experience (Core or Cloud) in production, including macros, incremental models, snapshots for SCD and history tracking, tests, exposures, and packages.
- Hands-on experience with Sigma Computing on Snowflake, including workbook design, data modeling, performance tuning, and governance.
- Deep knowledge of the mortgage domain: loan lifecycle, servicing, MSRs (base/excess strips), whole loans, non-agency/non-QM, RTL/fix-and-flip, securitization, and investor reporting.
- Working understanding of capital markets concepts such as pool and deal structures, cash flows, prepayment and default metrics (CPR, CDR, severity), and valuation inputs.
- Strong SQL and data modeling skills (dimensional, Data Vault, or hybrid), plus Python.
- Experience with a cloud platform (Azure preferred; AWS acceptable), including storage integration, networking, and identity.
- Track record of building reconciliation and data quality controls in a financial services setting.
- Excellent communication skills and comfort working directly with senior business stakeholders.
- Experience with data from subservicers such as Newrez/Shellpoint, Mr. Cooper, or PHH, and with trustee and vendor data (Intex, CoreLogic, Black Knight/ICE, eMBS).
- Familiarity with MSR valuation workflows and vendors (e.g., RiskSpan, MIAC).
- Snowflake SnowPro Advanced: Architect certification.
- dbt Analytics Engineering certification.
- Experience migrating reporting from Excel, Tableau, or Power BI to Sigma.
- Experience with dbt Semantic Layer/MetricFlow or other shared metric definitions consumed by Sigma.
- Exposure to Snowflake Cortex, Snowpark ML, or feeding data to LLM/agent-based applications.
- Background at a mortgage REIT, servicer, investment bank, or mortgage fintech.
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