- 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
- Were building, not maintaining - cant just delegate
- Credibility comes from doing: "Heres how Id architect this... let me show you"
- Examples of What Youll 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 youre building:
- Run "Lakehouse Office Hours" (teach business users how to leverage the platform)
- Create demos and proof-of-concepts to show whats 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)
- 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 (youll 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 Youll 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!
