Data Architect – Mortgage & Capital Markets

Data Architect – Mortgage & Capital Markets

Location: Mostly remote; occasional onsite meetings in NYC

Core stack: Snowflake, dbt, Sigma Computing

*Key Responsibilities*

- Own the end-to-end architecture of the Snowflake data warehouse, including account and database design, layered data modeling (raw, curated, consumption), 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 and 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 (staging, intermediate, marts), 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.

*Required Qualifications*

- 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. This includes 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.

*Preferred Qualifications*

- 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