
Data Software Engineer
4 days ago
Purpose of the role
As a Software Development Engineer, you will work with airline and rail customers to analyze, develop, test, and deploy data solutions in both test and production environments. You'll collaborate with internal teams, including developers, architects, engineers, customer account teams, project managers, and operations, to deliver tailored data services and backend integration solutions.
In this role you'll:
- Develop and maintain high-quality software applications that meet user and business needs.
- Write reliable and efficient code that aligns with industry and Navitaire Services standards.
- Design and implement maintainable software architectures for small to medium-sized systems.
- Identify and resolve technical issues, including those in production environments.
- Test and debug software thoroughly to ensure performance and reliability.
- Create and maintain technical documentation for reference and reporting.
- Work closely with cross-functional teams, including product managers, business analysts, operations groups, and senior engineers, to define software requirements and deliver high-quality solutions.
- Stay updated with the latest technologies and industry trends, incorporating them into the development process to improve efficiency and effectiveness.
About the Ideal Candidate
- Holds a degree in Computer Science, Computer Engineering, Information Technology, Systems Information, Mathematics, Data Science, or has equivalent experience.
- Has at least 2 years of experience in software development within an Agile environment.
- Has at least 1 year of experience with data technologies (e.g., SQL, NoSQL, DBMS, BI and Analytics).
Has experience with:
C# / .NET programming
- API integration and implementation
- Unit testing
- Communicates effectively in English (verbal and written) and works well with customers from diverse backgrounds.
Preferred Qualifications
Familiarity with:
Reporting and analytics tools (e.g., SQL Server Reporting Services, Power BI, Databricks)
- Data integration tools (e.g., SQL Server Integration Services, Azure Data Factory)
- Database performance tuning and development
- Cloud data storage (e.g., Azure SQL, Cosmos, Splunk)
- Test automation frameworks (e.g., xUnit, NUnit)
- Cloud deployment (Azure preferred, AWS considered)
- Microservice-based architecture
- External API design
- CI/CD automation and advanced testing (integration, performanc
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