Senior Developer – Connected Customer (Loyalty Platform)

About the role

Build the customer experiences that keep millions coming back. We're looking for a Senior Developer to join our Connected Customer Team, where you'll play a key role in building and enhancing the technology behind our Loyalty Program.

Responsibilities

• Design, develop, and support cloud-native services for our Loyalty Engine, CRM integrations, Order History, and customer-facing APIs.
• Build scalable Java microservices using Spring Boot and Azure cloud technologies.
• Develop and maintain Backend-for-Frontend (BFF) services that support digital customer experiences.
• Partner with Payments, Marketing, and other engineering teams to design secure, reliable service integrations.
• Build and optimize data pipelines using Azure Data Factory and related technologies.
• Support integration testing and application hardening leading up to major customer-facing releases.
• Write advanced SQL queries and support data modeling initiatives.
• Provide technical leadership by mentoring developers, reviewing code, and helping prioritize work.
• Collaborate with business stakeholders to translate requirements into scalable technical solutions.
• Create and maintain technical documentation, architecture diagrams, and development standards.

Requirements

• Bachelor's degree in Computer Science, Engineering, or equivalent experience.
• 7+ years of software development experience.
• 2+ years developing and deploying Java applications in Microsoft Azure.
• Strong experience with: Java 8+, Spring Boot, Maven or Gradle, Git.
• Experience with Azure services including App Service, Functions, Storage, Key Vault, Cosmos DB, Event Hubs, and Service Bus.
• Experience building ETL processes or Azure Data Factory pipelines.
• Strong understanding of data modeling and operational data management.
• Experience designing or consuming Backend-for-Frontend (BFF) APIs.
• Experience integrating payment processing solutions, gateway APIs, and tokenization services.
• Experience integrating CRM platforms such as Salesforce, Microsoft Dynamics, or similar customer engagement platforms.
• Experience building scalable microservices in distributed environments.
• Familiarity with DevOps tools such as GitHub, Kubernetes, Jenkins, and SonarQube.
• Excellent communication, analytical, and problem-solving skills.
• Ability to thrive in a collaborative, fast-paced environment with multiple concurrent initiatives.

Qualifications

• Required Qualifications: Bachelor's degree in Computer Science, Engineering, or equivalent experience. 7+ years of software development experience. 2+ years developing and deploying Java applications in Microsoft Azure. Strong experience with Java 8+, Spring Boot, Maven or Gradle, Git. Experience with Azure services including App Service, Functions, Storage, Key Vault, Cosmos DB, Event Hubs, and Service Bus. Experience building ETL processes or Azure Data Factory pipelines. Strong understanding of data modeling and operational data management. Experience designing or consuming Backend-for-Frontend (BFF) APIs. Experience integrating payment processing solutions, gateway APIs, and tokenization services. Experience integrating CRM platforms such as Salesforce, Microsoft Dynamics, or similar customer engagement platforms. Experience building scalable microservices in distributed environments. Familiarity with DevOps tools such as GitHub, Kubernetes, Jenkins, and SonarQube. Excellent communication, analytical, and problem-solving skills. Ability to thrive in a collaborative, fast-paced environment with multiple concurrent initiatives.
• Preferred Qualifications: Microsoft Azure Developer Associate or Azure Data Engineer Associate certification. Experience with AWS or Google Cloud Platform. Experience supporting loyalty or rewards platforms. Knowledge of event-driven architecture using Event Hubs or Service Bus. Experience using AI-assisted development tools for coding, testing, or documentation. Experience with big data technologies such as Spark, Kafka, or Hadoop. Exposure to machine learning frameworks such as TensorFlow or PyTorch.