Snowflake Data Architect

This is a senior, hands-on architecture role responsible for designing and governing a scalable Snowflake data platform supporting mortgage servicing, Mortgage Servicing Rights (MSRs), capital markets, portfolio analytics, finance, operations, and investor reporting., n \n

• Own the end-to-end architecture of the Snowflake data platform, including account and database design, layered data architecture, security, performance, scalability, and cost governance. \n

• Design data models for mortgage and capital markets domains, including loan-level servicing, MSR portfolios, base and excess servicing, advances, remittances, prepayments, delinquencies, whole loans, and trade and settlement data. \n

• Design and build ingestion pipelines integrating data from subservicers, trustees, custodians, valuation vendors, internal systems, SFTP feeds, APIs, flat files, Excel, and cloud storage. \n

• Lead the transformation architecture using dbt, including staging, intermediate and mart layers, incremental models, macros, snapshots, testing, documentation, packages, CI/CD, and environment promotion. \n

• Build robust data-quality, reconciliation, and change-control frameworks, including tape-to-tape comparisons, servicer-to-investor reconciliations, exception management, and month-end MSR controls. \n

• Design and orchestrate data pipelines using Snowpark, Snowflake Streams/Tasks, Airflow, Azure Data Factory, and dbt. \n

• Design semantic and consumption-layer models in Snowflake supporting Sigma Computing, portfolio analytics, capital markets, finance, operations, risk, and valuation use cases. \n

• Partner with business teams to design and govern Sigma workbooks, dashboards, self-service analytics, input tables, and write-back workflows. \n

• Implement enterprise security using Snowflake RBAC, row-level security, masking policies, PII/NPI protection, audit logging, and Sigma security/governance. \n

• Support downstream data consumption for MSR valuation, risk models, investor reporting, analytics, and AI/LLM applications. \n

• Optimize Snowflake warehouse sizing, clustering, query performance, storage design, and credit utilization. \n

• Work directly with Capital Markets, Portfolio Analytics, Finance, and Operations stakeholders to translate complex mortgage workflows into scalable data architecture. \n

• Mentor data engineers and establish engineering standards across data modeling, development, testing, deployment, and documentation. \n

We are seeking a highly experienced Snowflake Data Architect with strong hands-on expertise in Snowflake, dbt, Sigma Computing, and mortgage/capital markets data., The ideal candidate will combine strong data architecture and engineering expertise with deep knowledge of mortgage servicing and capital markets workflows. Mortgage domain experience is a core requirement for this position., * 10+ years of experience in Data Engineering, Data Architecture, or related data-platform roles. \n

• 4+ years of hands-on experience designing and implementing production Snowflake platforms. \n

• 3+ years of hands-on dbt experience using dbt Core or dbt Cloud, including incremental models, macros, snapshots, tests, exposures, packages, documentation, and CI/CD. \n

• Hands-on experience with Sigma Computing on Snowflake, including workbook development, data modeling, performance optimization, and governance. \n

• Strong mortgage-domain experience covering the loan lifecycle, mortgage servicing, MSRs, base/excess servicing strips, whole loans, Non-Agency/Non-QM, RTL/Fix-and-Flip, securitization, and investor reporting. \n

• Strong understanding of capital markets concepts including pool/deal structures, cash flows, prepayment and default behavior, CPR, CDR, severity, and valuation inputs. \n

• Advanced SQL, Python, and data-modeling skills, with experience using dimensional, Data Vault, or hybrid modeling approaches. \n

• Experience with a major cloud platform, preferably Microsoft Azure, including storage integration, networking, identity, and security. \n

• Demonstrated experience implementing financial-services data reconciliation, controls, and data-quality frameworks. \n

• Strong communication skills with the ability to work directly with senior technical and business stakeholders. \n, * Experience working with mortgage data from Newrez/Shellpoint, Mr. Cooper, PHH, or similar subservicers. \n

• Experience with trustee, market, or mortgage data providers such as Intex, CoreLogic, Black Knight/ICE, or eMBS. \n

• Familiarity with MSR valuation workflows and platforms such as RiskSpan or MIAC. \n

• Snowflake SnowPro Advanced: Architect certification. \n

• dbt Analytics Engineering certification. \n

• Experience migrating reporting and analytics from Excel, Tableau, or Power BI to Sigma. \n

• Experience with dbt Semantic Layer / MetricFlow or centralized metric definitions. \n

• Exposure to Snowflake Cortex, Snowpark ML, LLMs, or agent-based applications. \n

• Previous experience within a Mortgage REIT, mortgage servicer, investment bank, mortgage fintech, or capital markets organization. \n, The successful candidate should be comfortable operating as both a senior technical architect and a trusted partner to business stakeholders.