Senior Integration Engineer

Edray•Charlotte, NC

About The Position

We are seeking an experienced software engineer with a passion for distributed systems, cloud-native integrations, and data engineering to help build and evolve the technology platform powering EDRAY's nationwide logistics network. The Senior Integration Engineer is responsible for designing, developing, deploying, and supporting highly scalable integration services that connect EDRAY's platform with customers, carriers, terminals, chassis providers, transportation management systems, and other external partners. This role combines software engineering, cloud architecture, API development, data engineering, and platform reliability. The Senior Integration Engineer will build reliable, scalable, and maintainable solutions using modern cloud technologies, APIs, messaging platforms, event-driven architectures, and data engineering best practices. The ideal candidate enjoys solving complex technical problems, designing resilient systems, improving operational reliability, and taking ownership of production services throughout their entire lifecycle-from architecture and development through deployment, monitoring, incident response, and continuous improvement. The Senior Integration Engineer will work closely with Engineering, Operations, Product, Business Analysts, and external partners to automate business processes, improve data quality, and ensure seamless data exchange across the EDRAY ecosystem.

Requirements

Bachelor's degree in Computer Science, Information Systems, Software Engineering, or a related technical discipline (or equivalent professional experience).
5+ years of experience developing enterprise integrations, distributed applications, software platforms, or data engineering solutions.
Professional experience developing applications using Python.
Strong SQL skills including schema design, query optimization, troubleshooting, and data analysis.
Experience developing integrations using REST APIs, web services, and JSON/XML data formats.
Experience designing, developing, and supporting cloud-native applications on Microsoft Azure, Amazon Web Services (AWS), Google Cloud Platform (GCP), or a comparable cloud platform.
Experience working with messaging technologies, event-driven architectures, or asynchronous processing.
Strong understanding of distributed systems concepts including retries, dead-letter queues, fault tolerance, partial failures, and resilient application design.
Strong understanding of data engineering principles including data quality, schema evolution, deduplication, idempotency, reconciliation, and backfill strategies.
Experience with software engineering best practices including source control, code reviews, automated testing, and deployment processes.
Excellent analytical, troubleshooting, and problem-solving skills.
Strong written and verbal communication skills with the ability to communicate effectively with both technical and non-technical stakeholders.
Ability to manage multiple priorities while supporting business-critical systems.
Willingness to participate in an on-call rotation supporting production integration services.

Nice To Haves

Experience with Microsoft Azure services such as Azure Functions, Azure Service Bus, Azure Storage, Azure Monitor, and Application Insights.
Experience with AWS services such as Lambda, SQS, SNS, EventBridge, API Gateway, S3, CloudWatch, DynamoDB, or Step Functions.
Understanding of cloud architecture principles including serverless computing, event-driven architectures, identity and access management (IAM), networking, monitoring, scalability, and cost optimization.
Experience with Databricks, Apache Spark, Delta Lake, or other modern data engineering platforms.
Experience developing operational or administrative web applications using React and TypeScript.
Experience with Power BI or similar reporting and analytics platforms.
Experience with C#, .NET, or PowerShell.
Experience integrating with Microsoft Dynamics 365 Business Central.
Experience with EDI, SFTP, FTP, AS2, or B2B integration technologies.
Experience with CI/CD pipelines, automated testing, DevOps practices, and Infrastructure as Code.
Experience with Git, Azure DevOps, GitHub, or similar source control platforms.
Experience with AI-assisted software development, anomaly detection, predictive analytics, or applied machine learning.
Experience designing solutions capable of processing millions of records or supporting high-volume enterprise integrations.
Experience working in logistics, transportation, supply chain, or intermodal operations is beneficial but not required.

Responsibilities

Design, develop, deploy, and maintain customer, carrier, and partner integrations using EDRAY's configuration-driven integration platform.
Configure new partner integrations using reusable platform capabilities while extending platform functionality when new integration patterns are required.
Design and develop Python-based services running on Azure Functions.
Build inbound integration services supporting email, SFTP, Azure Service Bus, polling services, REST APIs, and event-driven architectures.
Develop outbound integrations supporting multiple delivery destinations and partner-specific requirements.
Integrate with REST APIs, EDI platforms, web services, SFTP endpoints, and internal applications while implementing secure authentication, pagination, retry logic, throttling, watermarking, and idempotent processing.
Apply engineering best practices including modular design, reusable components, clean code principles, design patterns, and maintainable architecture.
Participate in technical design reviews and contribute to long-term platform architecture decisions.
Migrate legacy integrations to EDRAY's modern integration platform while validating production results prior to implementation.
Design scalable integration architectures capable of supporting high transaction volumes and evolving business requirements.
Build cloud-native integration services leveraging Azure serverless computing, messaging, storage, monitoring, and event-driven technologies.
Design and maintain scalable data pipelines supporting customer and operational integrations.
Ensure platform reliability through resilient application design, fault tolerance, automated recovery processes, and proactive monitoring.
Optimize integrations for throughput, latency, scalability, and cloud resource efficiency.
Analyze system performance and identify opportunities to improve reliability, scalability, and operational cost.
Own and enhance the integration audit platform using Databricks and Apache Spark to provide complete visibility into integration processing and data movement.
Analyze operational data using Spark SQL to troubleshoot issues and support business reporting.
Develop automated monitoring, alerting, health checks, and operational dashboards for integration services.
Design observability solutions using Azure Monitor, Application Insights, logs, metrics, dashboards, and distributed tracing.
Improve platform scalability, resiliency, and maintainability through continuous engineering enhancements.
Design and maintain reliable data processing pipelines supporting enterprise integration workflows.
Ensure data quality through validation, reconciliation, deduplication, schema management, exception handling, and automated quality controls.
Develop solutions supporting schema evolution, data migration, historical backfills, and operational recovery.
Implement data integrity controls ensuring accurate movement of business-critical transportation and logistics information.
Build automated validation frameworks to ensure production-ready integrations.
Design integrations using secure software development practices.
Implement secure authentication methods including OAuth2, API keys, JWT, certificates, managed identities, and token-based authentication.
Protect customer and operational data through encryption, secrets management, and least-privilege access controls.
Follow secure coding standards and participate in vulnerability remediation activities.
Ensure integrations meet internal security and compliance requirements.
Develop and maintain CI/CD pipelines supporting automated builds, testing, deployment, and rollback processes.
Participate in Infrastructure as Code practices using tools such as Terraform, Bicep, or Azure Resource Manager templates.
Automate operational processes through scripting and engineering tools.
Participate in code reviews, pull requests, branching strategies, and software development lifecycle practices.
Maintain high-quality code through peer reviews, static analysis, automated testing, and continuous refactoring.
Contribute to engineering standards, documentation, and best practices.
Take ownership of integration services throughout their lifecycle including design, implementation, deployment, monitoring, incident response, and continuous improvement.
Monitor production integrations and proactively identify issues before customer impact occurs.
Investigate production incidents across the complete integration lifecycle including source systems, listeners, message queues, processing services, APIs, target systems, and audit logs.
Perform root cause analysis and implement corrective actions, automation improvements, and regression testing to prevent recurring issues.
Troubleshoot distributed system challenges including retries, dead-letter queues, partial failures, latency issues, and service dependencies.
Participate in production support and an on-call rotation supporting critical integration services.
Partner with Engineering, Operations, Product, Business Analysts, and external customers to gather technical requirements and deliver integration solutions.
Translate business requirements into scalable technical designs while identifying risks and clarifying ambiguous requirements before implementation.
Maintain and enhance operational tools used for monitoring, onboarding, queue management, traceability, and operational recovery.
Document integration designs, technical specifications, architecture decisions, operational procedures, and platform enhancements.
Participate in Agile/Scrum ceremonies, sprint planning, backlog refinement, and continuous improvement initiatives.
Mentor and support junior engineers through code reviews, technical discussions, and knowledge sharing.
Evaluate emerging technologies and recommend improvements to integration architecture and engineering practices.