Job Description

About the Role

We're building a modern data platform to power our mortgage lending and servicing platform from the ground up. As our Senior Data Architect, you'll be the technical visionary and hands-on builder who defines our data platform strategy and leads its execution.


This is a player-coach role where you'll architect solutions, write code, and lead a small engineering team (2-3 people) while partnering closely with our business-focused Senior Manager of Data Products & Analytics.


You're not just drawing architecture diagrams. You're building the platform, driving modernization, and making it real.

What We're Building:

Modernizing from legacy (SQL Server, .NET) to modern stack (Databricks, dbt, Sigma) Building 7 AI-powered product categories (borrower intelligence, investor analytics, employee copilots, document intelligence, compliance monitoring, automated decisioning, predictive analytics) Creating a data lakehouse that powers analytics and AI/ML products

Your Mission:

Be THE technical leader who makes this transformation happen Design the architecture, then build it yourself (with your small team) Drive adoption of modern data capabilities across the organization Partner with business leaders to deliver products that matter

What You Will Do:

Define the technical vision and roadmap: Create the modernization blueprint for our legacy A360 application (aging .NET app ? modern UI with embedded analytics) Design our lakehouse architecture on Databricks (medallion layers, data modeling, governance) Define the AI product architecture (how do 7 product categories integrate and share intelligence?) Support build vs buy vs partner decisions on technology Establish data platform standards, patterns, governance and best practices Design and build data pipelines (Databricks, dbt) Develop APIs and backend services for A360 modernization Build proof-of-concepts for AI products (LLM integrations, ML models) Write production-quality code (Python, SQL, dbt) Debug complex technical problems when your team is stuck Optimize performance (query tuning, pipeline efficiency, cost optimization) Team is small (2-3 engineers) - you need to code alongside them Complex problems need senior technical expertise We're building, not maintaining - can't just delegate Credibility comes from doing: "Here's how I'd architect this... let me show you" Examples of What You'll Build: dbt transformation pipelines for mortgage loan data Real-time data quality monitoring system Document classification and extraction engine (OCR + LLM) APIs for A360 modernized frontend Productionize AI and ML models Lead a small, focused engineering team: Manage 2-3 data engineers and 1 DBA Set technical priorities and remove blockers Code reviews and technical mentorship Develop team capabilities (upskill on modern stack) Balance team development with hands-on contribution Drive adoption of the platform you're building: Run "Lakehouse Office Hours" (teach business users how to leverage the platform) Create demos and proof-of-concepts to show what's possible Present to executives and business leaders (sell the vision) Train analysts and business users on self-service analytics (Sigma) Build internal advocates and champions Own data platform strategy and architecture (Databricks lakehouse, data modeling, governance) including operational databases. Build and optimize data pipelines Establish data quality framework (monitoring, alerting, anomaly detection) Manage production infrastructure (uptime, performance, cost optimization) Define security and compliance architecture (data access, audit trails, encryption) A360 Modernization (High Priority) Create technical blueprint for modernizing legacy A360 application Design API layer (modern frontend ? backend data services) Architecture for embedded analytics (Sigma widgets in A360 UI, LLM integration) Migration strategy (phased approach, parallel systems, SQL Server ? Databricks) Coordinate with application developers on frontend development

Team Development

Lead 2-3 data engineers in building platform capabilities Take over DBA responsibilities across operational databases Mentor team on modern data stack (Databricks, dbt, cloud architecture) Code reviews and technical guidance Build team culture of quality and ownership

What We are Looking for:

Databricks Expertise (Critical): 3+ years working with Databricks or similar platforms Deep understanding of lakehouse architecture (medallion patterns, data modeling, optimization) Experience with Delta Lake, Unity Catalog, Databricks SQL, MLFlow Know how to optimize for performance and cost

Data Engineering & Modern Stack:

Strong dbt experience (models, tests, documentation, orchestration) Python proficiency (data engineering, APIs, scripting, automation) SQL mastery (complex queries, optimization, performance tuning) Cloud platforms (AWS) Data pipeline orchestration (Airflow, Databricks Workflows, or similar)

Application Modernization:

Legacy system modernization experience (re-platforming old applications) API design and development (RESTful APIs, backend services) Understanding of frontend/backend separation patterns Phased migration strategies

Strategic Thinking + Execution:

Can create multi-month technical roadmaps and drive them to completion Have actually DRIVEN modernization initiatives (not just participated) Comfortable with ambiguity (figuring things out, not following playbooks) Balances pragmatism with technical excellence (ship good solutions, not perfect ones)

Communication & Evangelism:

Can explain technical concepts to non-technical people (executives, business users) Comfortable presenting and teaching (office hours, demos, training) Can "sell" the vision and drive adoption Strong written communication (architecture docs, technical proposals)

Ownership & Initiative:

Self-starter who takes end-to-end ownership Proactive problem-solver, not reactive Comfortable making decisions with incomplete information Track record of delivering results, not just talking about architecture Leadership (Player-Coach): Experience managing or leading small teams (2-5 people) Can mentor and develop engineers Comfortable balancing hands-on work with team leadership Collaborative partnership style (not territorial)

Nice-to-Haves:

Sigma or similar BI tools (Tableau, Looker, Power BI) SQL Server knowledge (you'll be migrating from it) .NET familiarity (helpful for A360 modernization) LLM/AI integration experience (GPT-4, Claude, prompt/context engineering) ML/data science background (model development, deployment) Financial services or mortgage industry experience

Tech Stack:

Legacy: SQL Server, .NET application (A360), SSIS pipelines, SSRS Modern: Databricks, dbt, Sigma, AWS

Future State (What You'll Build):

Lakehouse-first: Databricks as primary platform, SQL Server in maintenance mode Modern pipelines: dbt for transformations, batch and incremental loads, near-real-time where possible API-driven: RESTful APIs for A360 modernized UI AI/ML: LLM integrations (GPT-4, Claude), ML models for prediction Reporting/Analytics: Sigma for self-service, embedded analytics

What's in it for you?

Competitive compensation and full benefits package include medical, dental, and vision. 100% company-paid life insurance and disability coverage! 401K with company matching! 17 days PTO (increases with tenure) and 9 company paid holidays! Professional but fun, casual work environment and great team culture!

About BSI Financial

Founded in 1986, we provide financial services that support our vision of enabling sustainable home ownership by practicing core values that embody doing what is right; emphasizing problem solving; delivering on expectations and winning with humility. Our clients include lenders and investors who make home financing possible.


BSI Financial was ranked multiple times in the SMU Dallas 100 list of the fastest growing

companies in North Texas and was twice named to the Inc. 5000 list of the fastest growing U.S. companies.

EEO Statement

We are an equal employment opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, national origin, disability status, protected veteran status, or any other characteristic protected by law.