Sr. Software Developer

About the Role

Join our Digital Transformation Office as a Backend Engineer to architect and build scalable, production-grade applications that power Worldpac's digital evolution. You'll work at the intersection of modern web applications, enterprise data platforms, and AI/ML capabilities, building APIs and services that enable intelligent, data-driven experiences for our customers and internal teams.

This role offers the opportunity to establish foundational backend engineering standards and patterns while working alongside data engineers, data scientists, and frontend developers in a fast-paced innovation environment. You will work closely with data scientists, machine learning engineers, product managers, and other software engineers to turn business needs into robust technical solutions. This is a hands-on engineering role with clear ownership and responsibility for critical platform components.

What You'll Build

• Production APIs & Services: Design and implement RESTful APIs and microservices supporting React-based applications for customer engagement, promotional campaigns, pricing optimization, and business intelligence
• Enterprise Integrations: Build robust integration layers connecting modern applications with legacy systems (AS400), data platforms (Snowflake, Databricks), CRM (Salesforce), and third-party services
• Data Pipeline Interfaces: Create efficient interfaces for ML/AI model consumption, real-time analytics, and data-driven decision systems
• Platform Infrastructure: Establish backend architecture patterns, CI/CD pipelines, and DevOps practices that enable rapid, reliable delivery

Key Responsibilities

Architecture & Development

• Design scalable backend architectures using modern frameworks and cloud-native patterns
• Build high-performance APIs serving React frontends with proper authentication, authorization, and rate limiting
• Implement business logic layers that bridge application needs with enterprise data platforms
• Establish code quality standards, design patterns, and best practices for backend development

Integrations & Data Access

• Design and implement integration patterns for complex enterprise systems (AS400, Salesforce, SpeedDial catalog)
• Build efficient data access layers connecting to Snowflake (operational warehouse) and Databricks (analytics platform)
• Create real-time and batch integration pipelines using modern messaging/streaming technologies
• Implement proper error handling, retry logic, and monitoring for distributed systems

DevOps & CI/CD

• Establish comprehensive CI/CD pipelines using Azure DevOps, GitHub Actions, or similar platforms
• Implement infrastructure-as-code using Terraform, ARM templates, or similar tools
• Build automated testing frameworks (unit, integration, end-to-end) ensuring code quality
• Set up monitoring, logging, and alerting using Azure Monitor, Application Insights, or similar tools
• Manage containerized deployments using Docker and orchestration platforms

Collaboration & Leadership

• Work closely with data engineers and data scientists to consume ML models and analytics capabilities
• Partner with frontend developers to design intuitive, performant API contracts
• Collaborate with stakeholders to translate business requirements into technical solutions
• Mentor junior engineers and contribute to team knowledge sharing

Requirements

Must Have

• Qualifications: Bachelor’s degree in computer science, Engineering, or a related technical field, or equivalent practical experience.
• Backend Frameworks: 5+ years experience with Node.js/Express, Python/FastAPI, .NET Core, or Java/Spring Boot
• API Design: Expert-level RESTful API design, GraphQL experience a plus
• Cloud Platforms: Strong Azure experience (App Service, Functions, API Management, SQL Database, Key Vault, Service Bus)
• Databases: Proficiency with relational databases (SQL Server, PostgreSQL) and NoSQL (Cosmos DB, MongoDB)
• CI/CD: Hands-on experience building production pipelines with automated testing and deployment
• Version Control: Git workflows, branching strategies, code review processes (Bitbucket/GitHub)
• Security: Understanding of OAuth2/OIDC, API security best practices, secrets management

Strong Plus

• Experience integrating with data warehouses (Snowflake, Redshift) or analytics platforms (Databricks)
• Containerization and orchestration (Docker, Kubernetes, Azure Container Apps)
• Message queuing systems (Azure Service Bus, RabbitMQ, Kafka)
• Infrastructure-as-Code (Terraform, Pulumi, ARM/Bicep)
• Experience with legacy system integrations (mainframes, AS400)
• Microservices architecture patterns and distributed systems
• Performance optimization and caching strategies (Redis, CDN)
• Experience in e-commerce, supply chain, or B2B platforms

Nice to Have

• Familiarity with ML model serving patterns and APIs
• Experience with real-time analytics and event-driven architectures
• Knowledge of automotive industry or parts distribution
• Exposure to React/TypeScript for full-stack understanding
• Experience with API documentation tools (Swagger/OpenAPI, Postman)

What This Role Offers

• Ownership of key backend systems that form the foundation of our data and AI products.
• Close collaboration with experienced engineers, data scientists, and product leaders.
• The opportunity to shape platform architecture and engineering standards.
• A professional environment that values structured thinking, high-quality work, and continuous improvement.

Why Join Worldpac's DTO Team?

Impact & Ownership

• Ground-floor opportunity to establish backend engineering standards for a transforming enterprise
• Direct impact on products serving ~55,000+ customers and ~$2.5B in annual revenue
• Freedom to choose technologies and patterns that you believe are best

Growth & Learning

• Work alongside data engineers, data scientists, and ML engineers building AI-powered capabilities
• Exposure to modern data platforms, ML/AI integration, and enterprise architecture
• Opportunity to shape engineering culture and practices

Technology & Innovation

• Modern cloud-native architecture with Azure
• Real-world challenges integrating cutting-edge AI with legacy enterprise systems
• Support for professional development, certifications, and continuous learning

Our Engineering Principles

• Production-grade from day one: We build for scale, reliability, and maintainability
• Measurable business value: Every system we build drives clear business outcomes
• Strategic positioning: We favor solutions that give us control, flexibility, and competitive advantage
• Continuous improvement: We iterate, learn, and evolve our practices