Java Software Engineer

Candidates need to have 10 years experience, and 5 years in engineering software solutions using Java, Spring boot.

Core Characteristics and Soft Skills:

Beyond technical proficiency, the right mindset and interpersonal skills are crucial for success on our team. We’d prioritize candidates who demonstrate:

• Problem-Solving Acumen: The ability to analyze complex problems, break them down, evaluate different approaches, and implement robust, efficient solutions. This includes troubleshooting existing systems and designing new ones.
• Independence and Initiative: We value engineers who can take ownership of tasks, research potential solutions independently, make informed decisions, and drive work forward with minimal supervision once objectives are clear.
• Dependability and Accountability: Team members must be reliable, meet commitments, deliver high-quality work, and take responsibility for their contributions.
• Strong Communication Skills: Clear, concise communication (both written and verbal) is essential. This includes explaining technical concepts to varied audiences, actively listening, providing constructive feedback, and documenting work effectively.
• Collaboration and Teamwork: Ability to work effectively within a team structure, share knowledge, participate in code reviews, and contribute to a positive team dynamic.
• Adaptability and Eagerness to Learn: The technology landscape and business needs evolve. We seek individuals who are curious, adaptable, and willing to learn new technologies and methodologies.

Core Technical Skillset:

Our current technology stack forms the foundation of our work. Proficiency or strong experience in the following areas is highly desirable:

• Backend Development:
  • Java: Deep understanding of Java (latest LTS versions preferred).
  • Spring Boot: Extensive experience building applications and microservices using the Spring Boot framework and its ecosystem (e.g., Spring Data, Spring Security, Spring Cloud).
• Messaging Systems:
  • Apache Kafka: Solid understanding of Kafka concepts (topics, producers, consumers, partitioning, brokers) and experience building event-driven systems.
• Containerization & Orchestration:
  • Kubernetes: Practical experience deploying, managing, and troubleshooting applications on Kubernetes.
  • OCP (OpenShift Container Platform): Experience specifically with OpenShift is a significant advantage.
  • AKS (Azure Kubernetes Service): Experience with AKS is also highly relevant.
  • (General Docker knowledge is expected)
• CI/CD & DevOps:
  • GitHub Actions: Proven experience in creating, managing, and optimizing CI/CD pipelines using GitHub Actions for build, test, and deployment automation.
  • Understanding of Git branching strategies and DevOps principles.
• Frontend Development:
  • JavaScript: Strong proficiency in modern JavaScript (ES6+).
  • React: Experience building user interfaces with the React library and its common patterns/ecosystem (e.g., state management, hooks).
• Database & Data Warehousing:
  • Oracle: Experience with Oracle databases, including writing efficient SQL queries, understanding data modeling, and potentially PL/SQL.
  • Snowflake: Experience with Snowflake cloud data warehouse, including data loading, querying (SQL), and understanding its architecture.
• Scripting:
  • Python: Proficiency in Python for scripting, automation, data manipulation, or potentially backend API development (e.g., using Flask/Django, though Java/Spring is primary).

Domain Understanding (Transportation & Logistics):While not strictly mandatory, candidates with experience or a demonstrated understanding of the transportation and logistics industry (e.g., supply chain management, freight operations, warehousing, fleet management, routing optimization, TMS systems) will be able to contribute more quickly and effectively. They can better grasp the business context and user needs.Additional Valuable Skills:We are also interested in candidates who may possess skills in related areas that complement our core activities:

• Data Science & Analytics:
  • Experience with data analysis techniques.
  • Knowledge of Machine Learning (ML) concepts and algorithms (particularly relevant for optimization, forecasting, anomaly detection in logistics).
  • Proficiency with Python data science libraries (Pandas, NumPy, Scikit-learn).
  • Experience with data visualization tools and techniques.
  • Understanding of optimization algorithms (linear programming, vehicle routing problem algorithms, etc.).
• Cloud Platforms: Broader experience with cloud services (particularly Azure, but also AWS or GCP) beyond Kubernetes (e.g., managed databases, serverless functions, monitoring services).
• Testing: Strong experience with automated testing practices and tools (e.g., JUnit, Mockito, Cypress, Selenium, Postman/Newman).
• API Design & Management: Deep understanding of RESTful API design principles, API security (OAuth, JWT), and potentially experience with API gateways.
• Monitoring & Observability: Experience with tools like Prometheus, Grafana, ELK Stack (Elasticsearch, Logstash, Kibana), Datadog, Dynatrace, etc., for monitoring application health and performance.
• Security: Awareness and application of secure coding practices (e.g., OWASP Top 10).