Lead Engineer, Pricing & Decision Systems
One Park Financial11 days ago
Salt Lake City, UT, USAStaff+
Responsibilities
- Own and develop the Python-based pricing and decision engine and its production AWS services.
- Implement scoring models, pricing rules, offer grids, modifiers, and offer-construction logic from Data Science specifications.
- Lead and mentor engineers, set architecture and coding standards, review pricing-related changes, and direct team execution.
- Own data correctness in DynamoDB and S3, including audit records, experiment history, versioned reference files, reconciliation, and quality checks.
- Design, run, and analyze A/B tests for pricing strategies and maintain clean experiment data.
- Integrate the pricing engine with the sales platform, CRM, and external credit and bank-data providers.
- Maintain system reliability, observability, production health dashboards, deployment workflows, and incident-response coordination.
- Partner cross-functionally with Product, DevOps, Data Engineering, Data Science, and QA.
- Integrate machine-learning model outputs into production and build future analytics applications, data products, storage, pipelines, and quality checks.
- Use modern AI and LLM tooling to accelerate prototyping, documentation, testing, and delivery.
Requirements
- 5+ years of professional Python development building and maintaining production applications and services.
- Experience leading or mentoring engineers, setting standards, reviewing code, and directing a small team’s work.
- Experience building and maintaining REST APIs with FastAPI, Flask, or similar technologies.
- Hands-on production AWS experience, particularly with ECS/Fargate, DynamoDB, S3, Lambda, SQS, Secrets Manager, and CloudWatch.
- Experience designing DynamoDB access patterns, handling schema and type changes, and managing versioned S3 data including Parquet and partitioned datasets.
- Strong SQL skills and experience with relational and NoSQL data and CSV or Parquet reference files.
- Experience implementing business-logic-heavy applications where correctness and rule interpretation are critical.
- Familiarity with Pydantic or similar data-modeling and validation frameworks, plus reconciliation and QA checks.
- Experience integrating machine-learning or analytical model outputs into production, including feature engineering, scoring logic, and collaboration with Data Science.
- Experience designing or supporting A/B tests and experimentation, including stratification and experiment-data integrity.
- Strong communication, cross-team collaboration, self-direction, and end-to-end system ownership.
- Comfort using modern AI and LLM tools.
- Preferred: financial services, lending, or pricing experience; Salesforce or HubSpot APIs; Docker and CI/CD; dbt or Airflow; Next.js or TypeScript; RAG, LangChain, LangGraph, Agents SDK; and MLflow or SageMaker.
Benefits
- Local and national health insurance, dental and vision insurance, Group Medical Bridge, 401(k) with match, company-paid identity protection and life insurance, generous PTO, and holidays.
- Full-time, on-site position in Salt Lake City, United States.
Tech Stack
Categories
BackendData Engineering