Software Engineer-Remote

Role overview

Workplace

• Remote work is available from anywhere within the United States.
• Hires in the Minneapolis or Washington, D.C. area must work in the office at least four days per week.
• Remote employees must follow the employer's telecommuter policy.

Core responsibilities

• Build backend applications, REST APIs, and microservices for the Identity Management rebuild and existing application.
• Develop Python services and PySpark distributed processing workflows using Azure Databricks and Azure Data Factory.
• Define API contracts, models, error handling, versioning, and documentation using OpenAPI or Swagger.
• Implement resilient service communication, retries, timeouts, idempotency, asynchronous processing, and graceful failure handling.
• Create automated tests and integrate quality checks into CI/CD pipelines.
• Implement observability through logging, metrics, tracing, alerting, and dashboards.
• Apply secure coding, access controls, secrets management, encryption, and privacy-by-design.
• Troubleshoot production issues and improve reliability, performance, scalability, and cost efficiency.
• Use Git-based engineering, code reviews, automated builds, release controls, and deployment workflows.
• Apply approved AI tools and custom agents to engineering and operational work; collaborate across technical teams.

Required qualifications

• 5+ years building and operating enterprise applications, backend services, APIs, or microservices; 5+ years hands-on Python experience.
• 3+ years developing REST APIs and 3+ years using PySpark for distributed processing, transformation, validation, and tuning.
• 2+ years with Azure Databricks or similar distributed data platforms; 2+ years with relational and NoSQL databases, data modeling, and SQL.
• Experience designing microservices for scalability, resilience, and operational support.
• Experience with pytest or similar automated testing, including unit, integration, API, and regression testing.
• Git, code review, branching, CI/CD, release management, and production support experience.
• Docker experience and working understanding of Kubernetes or managed container platforms.
• Production experience with logging, monitoring, alerting, metrics, and distributed tracing.
• Understanding of software design, cloud security, identity/access management, data privacy, governance, and enterprise compliance.
• Strong problem-solving, root-cause analysis, troubleshooting, communication, and collaboration skills.

Preferred qualifications

• Event-driven architecture and Kafka, Azure Event Hubs, Azure Service Bus, or comparable messaging platforms.
• Performance testing, capacity planning, secure development lifecycle practices, and cloud cost optimization.
• Identity management, identity resolution, consumer/member profiles, or entity-resolution applications.
• Azure Data Factory pipeline orchestration and custom AI agent development or support.
• Healthcare, insurance, consumer profile, or enterprise identity data experience.
• Caching, API gateways, load balancing, rate limiting, asynchronous programming, and high-availability design.

AI usage expectations

• Demonstrate baseline proficiency with approved AI tools such as GitHub Copilot, Microsoft 365 Copilot, and Databricks Genie where applicable.
• Use AI responsibly for coding, code review, tests, documentation, debugging, analysis, monitoring, and delivery quality.
• Follow enterprise guidance for responsible AI, data protection, human review, security, and software quality.

Compensation

• Annual salary range is USD 72,800–130,000 for full-time employment; pay depends on factors including location, education, experience, and certifications.