The posting
Job Summary The Sr Enterprise Data Architect owns the design of Planet’s enterprise data architecture and is accountable for the technical blueprint that makes loan-level data accurate, traceable, and reusable across originations, servicing, capital markets, finance, and risk. This role defines how data is modeled, integrated, secured, and consumed, and holds the line on those standards as the platform scales. Essential Duties and Responsibilities
Own the enterprise data architecture and target-state design. Define the layered (medallion) architecture on Snowflake spanning raw, conformed, and curated layers; establish the reference architecture for ingestion, transformation, orchestration, and consumption; and maintain the architectural roadmap that sequences migration off legacy and redundant data stores. Design and own the enterprise data model and semantic layer. Build conformed dimensional and normalized models covering loan, borrower, property, investor, servicing, and financial subject areas. Define certified metric logic, grain, and business keys so that origination volume, pull-through, margin, delinquency, and servicing performance resolve to one set of numbers across the enterprise. Architect source system integration and data acquisition. Define ingestion patterns and contracts for the loan origination system, servicing platform, capital markets, vendor, and third-party sources, including change data capture, secure data sharing, API and file-based feeds, replay and late-arriving data handling, and schema evolution. Establish integration standards that survive vendor release cycles and upstream schema changes. Embed governance, security, privacy, and regulatory requirements into the architecture. Define critical data elements, lineage, and data quality control points; design classification, masking, tokenization, and role-based access patterns for NPI and PII; and ensure the architecture supports investor, agency, and regulatory reporting obligations, audit traceability, and retention requirements. Set and enforce engineering and architecture standards. Define modeling conventions, naming, transformation patterns, version control, testing, CI/CD, environment promotion, and observability requirements. Lead design reviews, mentor data engineers and analytics engineers, and produce the architecture documentation, decision records, and reference implementations the team builds against. Partner with business, technology, and vendor stakeholders. Translate business and regulatory requirements into architectural decisions, advise application development and information security on data-impacting changes, participate in platform and tooling evaluations, and represent the data architecture in enterprise governance and vendor technical forums. Performs other duties as assigned.
Position Requirements Education
Bachelor’s degree in Computer Science, Information Systems, Engineering, Mathematics, or a related field required. Advanced degree or relevant cloud data platform certification preferred.
Experience
Minimum ten (10) years of progressive experience in data engineering, data warehousing, or data architecture. Minimum four (4) years in a data architect or lead data modeler capacity, accountable for enterprise or domain-level architecture decisions.
Mortgage or consumer lending data experience strongly preferred, including familiarity with loan origination and servicing data, the loan lifecycle, and investor or agency delivery.
Demonstrated experience designing and delivering a cloud data warehouse in production, including source onboarding, layered transformation architecture, and downstream analytics consumption.
Hands-on experience building dimensional and normalized data models that survive contact with real source system data.
Experience integrating vendor-hosted systems of record through change data capture, secure data sharing, APIs, or replicated data feeds.
Experience implementing data quality, lineage, and access controls in a regulated environment subject to audit or examination.
Experience migrating or consolidating legacy reporting databases and semantic layers onto a modern cloud platform preferred.
Experience preparing data assets for machine learning or AI consumption preferred.
Functional/Technical Skills
Expert-level SQL and deep working knowledge of Snowflake or a comparable cloud data platform, including warehouse sizing, clustering, secure data sharing, and cost management. Strong command of data modeling technique, including dimensional modeling, slowly changing dimensions, data vault or normalized patterns, grain definition, business key management, and historization.
Proficiency with modern transformation and orchestration tooling, including dbt, workflow orchestration, Git-based version control, and CI/CD for data pipelines.
Working knowledge of mortgage origination and servicing data structures, including loan-level data, milestone and status data, document and condition data, escrow and payment data, and remittance and investor reporting data.
Familiarity with mortgage data and delivery standards such as MISMO, ULDD, and agency and investor reporting formats preferred.
Understanding of regulatory reporting requirements applicable to mortgage lending, including HMDA and fair lending data, and the data lineage evidence those requirements demand.
Knowledge of data privacy and protection requirements as applied to consumer financial data, including GLBA, CCPA/CPRA, and FCRA, and the architectural controls that satisfy them.
Experience defining and instrumenting data quality controls, reconciliation, and observability for business-critical data delivery.
Proficiency with a programming or scripting language used in data engineering, such as Python.
Working knowledge of BI and semantic layer design, including Power BI or comparable platforms, and certified metric governance.
Ability to produce clear architecture documentation, data flow diagrams, and decision records that both engineers and business stakeholders can use.
Strong communication skills, with the ability to defend a design decision to engineers and explain its business consequence to executives.
Environmental/Physical Demands Work is typically performed in a standard office environment. The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. While performing the duties of this job, the employee is regularly required to sustain predictable work attendance, communicate with others, frequently required to stand, walk, sit, and use arms, hands and fingers to reach, handle or touch. The employee must occasionally lift and/or move up to 10 pounds. Specific vision abilities required by this job include close vision, and ability to adjust focus. Pursuant to the Americans with Disabilities Act, reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. This job description is not designed to cover or contain a comprehensive listing of all activities, duties or responsibilities that are required of an employee. The Company reserves the right to amend or modify this document at any time and without notice.
