Backend Software Engineer

APN Consulting is supporting a confidential healthcare client hiring a Backend Software Engineer. The role builds and maintains secure backend integrations, APIs, and data pipelines connecting web applications with healthcare and other third-party systems.

Responsibilities:

• Design, build, and maintain APIs, data services, and microservices that securely exchange data with internal systems and external partners
• Develop effective data models, data flows, and pipelines to support reliable storage, transformation, and transfer of data across systems
• Integrate third party systems and tools through real time custom or standardized interfaces
• Implement secure integrations with third-party platforms, SaaS products, and cloud-based services
• Collaborate with cross-functional technical and business teams to understand requirements and translate them into practical, maintainable engineering solutions
• Drive feature development from requirements refinement, design, implementation and maintenance. Providing sound architecture and alignment with established standards
• Contribute to a DevOps culture through automated testing, source control, deployment automation, monitoring, and continuous improvement of development and delivery processes
• Participate in code reviews, technical design discussions, and architecture decisions
• Continuously document code, technical designs, framework standards, data processes, and team practices
• Troubleshoot complex data, application, integration, and performance issues and develop sustainable solutions

Requirements:

• Bachelor's degree in computer science, engineering or a related technical field
• 3-8 years of experience in enterprise or commercial software development and solution integrations
• Experience integrating with EMR/EHR systems like Athena, ECW and/or Epic
• Demonstrated experience developing data-intensive products using database technologies such as SQL Server, PostgreSQL and Cosmos
• Expertise in developing and integrating REST APIs, GraphQL interfaces, webhooks, web sockets and pub/sub technologies
• Strong SQL skills and the ability to design and code complex query logic and data transformation workflows
• Professional development experience with at least one procedural or object-oriented programming language
• Experience with cloud platforms and data services
• Experience with source control and software development practices
• Experience working with healthcare data
• Software Engineering: Applies sound software engineering principles to develop clean, maintainable, testable, and scalable solutions. Able to work independently and develop complete and robust features
• Data Engineering: Demonstrates strong understanding of data ingestion, transformation, integration, storage, data quality, and data lifecycle management
• Database Expertise: Understands database architecture, SQL development, query optimization, indexing, data modeling, and performance tuning
• Cloud & Architecture: Effectively evaluates and applies cloud services, distributed architectures, object-oriented design principles, and resiliency patterns
• Problem Solving: Breaks down complex technical problems, evaluates alternatives, and develops pragmatic solutions based on business and technical requirements
• Delivery Focus: Prioritizes shipping useful, sustainable solutions while remaining aware of scalability, maintainability, and technical debt
• Collaboration: Works effectively with software engineers, data engineers, analysts, data scientists, architects, and business stakeholders
• Communication: Clearly communicates technical concepts, design decisions, risks, and recommendations in both written and verbal formats
• Ownership & Accountability: Takes ownership of individual work and contributes to shared team outcomes, including successes, challenges, and continuous improvement
• Documentation: Consistently documents code, designs, processes, standards, and technical decisions
• preferably including multiple languages such as Scala, Typescript, C#, Java or Python
• preferably within Azure and/or AWS environments
• preferably including Git and automated build/deployment processes
• Enterprise Data Warehouse, Data Lake, Big Data, unstructured data, or in-memory data store technologies
• NoSQL databases such as MongoDB, Cassandra or Cosmos DB
• Cloud-based data movement and management using technologies such as Azure Data Factory, Azure Blob Storage, Azure Service Bus, Kafka, Redis, Amazon S3, AWS Glue, Azure Automation, machine learning services, or Elasticsearch
• Distributed data processing technologies such as Spark or Hadoop