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