Software Engineer Java

Key Responsibilities

1. Design and implement resilient scalable backend services using Java 17 and modern frameworks tailored to logistics use cases such as order fulfillment shipment tracking and fleet management.

2. Develop high-throughput APIs and event-driven data pipelines to integrate with logistics-specific systems (OMS WMS TMS GPS trackers and third-party carrier APIs) and ensure real-time data flow across the supply chain.

3. Lead architecture optimization initiatives: conduct performance audits of logistics backend systems identify bottlenecks (e.g. peak-season order surges real-time tracking latency) and design targeted improvements to enhance scalability reliability and cost-efficiency.

4. Refactor legacy logistics monoliths into modular cloud-native microservices balancing short-term performance needs with long-term maintainability and alignment with industry best practices.

5. Collaborate with product operations and DevOps teams to implement CI/CD pipelines infrastructure as code (IaC) and cloud deployment strategies that support 24/7 uptime for mission-critical logistics workflows.

6. Lead technical design discussions make architecture decisions for logistics-specific scenarios (e.g. route optimization algorithm integration geospatial data processing) and mentor junior developers to build team capability.

7. Ensure system compliance with logistics industry regulations (e.g. data privacy for shipment information EDI standards) and implement robust security measures for sensitive supply chain data.

8. Participate in code reviews drive adoption of coding standards and leverage observability tools to monitor and troubleshoot logistics system performance during peak operational periods.

Required Qualifications & Skills

Technical Expertise

1. Core Java & Frameworks

5 years of professional experience in Java backend development with a focus on building distributed systems for high-volume real-time use cases.

Proficiency in Java 17 deep understanding of modern Java features (virtual threads sealed classes pattern matching) to optimize performance for logistics workloads.

Expertise in Spring ecosystem: Spring Boot 3.x Spring Cloud (microservices orchestration) Spring Data JPA/ MongoDB and Spring Security 6.x (OAuth2 JWT) for securing supply chain data.

2. Distributed Systems & Messaging (Logistics-Focused)

Hands-on experience with message brokers: Apache Kafka (event streaming for shipment status updates order events) or RabbitMQ (queue management for warehouse operations).

Knowledge of distributed caching: Redis (caching route optimization results real-time fleet status) or Caffeine to reduce latency for frequent queries.

Understanding of service discovery & configuration management: Apache Nacos or Spring Cloud Config to manage dynamic configurations for multi-region logistics deployments.

3. Databases & Data Storage

Expertise in relational databases: PostgreSQL 16 MySQL 8 (query optimization for order/shipment data transaction management for inventory updates).

Experience with NoSQL databases: MongoDB (document modeling for unstructured logistics data like shipment notes) or Cassandra (high-write workloads for GPS tracking logs).

4. Cloud & DevOps

Hands-on experience with major cloud platforms: AWS (ECS/EKS for containerized logistics services S3 for shipment document storage RDS for database management) or Azure (AKS App Service).

Proficiency in Docker and Kubernetes for orchestrating microservices that support distributed logistics operations across regions.

Experience with CI/CD pipelines: Jenkins GitHub Actions or GitLab CI to enable rapid reliable releases for time-sensitive logistics workflows.

5. Observability & Monitoring

Familiarity with APM tools: Apache SkyWalking Prometheus Grafana or Datadog to monitor system performance track shipment processing latency and identify bottlenecks during peak seasons.

Logging & tracing: ELK Stack (Elasticsearch Logstash Kibana) or OpenTelemetry to troubleshoot issues in distributed logistics systems.

6. Modern Development Practices & Architecture Optimization

Strong understanding of microservices domain-driven design (DDD) and event-driven architecture (EDA) to model complex logistics domains (e.g. order lifecycle fleet management).

Ability to analyze system metrics conduct basic load testing and implement foundational optimizations (connection pooling query tuning) to handle logistics peak loads (e.g. holiday shipping surges).

Knowledge of API design: RESTful APIs gRPC or GraphQL for integrating with TMS/WMS systems and third-party carrier APIs; experience optimizing API latency for real-time tracking.

Experience with software quality tools: SonarQube (code quality) JUnit 5 Mockito (unit testing) TestContainers (integration testing) to ensure reliability of logistics-critical systems.

Soft Skills

1. 5 years of professional experience in Java backend development with a proven track record of building scalable distributed systemswith 1 years of direct experience in the logistics or supply chain industry preferred.

2. Strong problem-solving skills to address logistics-specific technical challenges (e.g. real-time data synchronization across geographically distributed warehouses handling high-volume shipment transactions).

3. Excellent communication and collaboration skills with experience working with cross-functional teams (product operations carrier partners) in a logistics environment.

4. Proactive mindset with a passion for learning and adopting new technologies to solve complex supply chain problems.

5. Bachelors or Masters degree in Computer Science Software Engineering or a related field (or equivalent professional experience).

be fluent in English Speaking/Writing

Preferred Qualifications

1. Knowledge of serverless computing: AWS Lambda or Azure Functions to build cost-efficient event-driven solutions for logistics use cases (e.g. shipment status notifications delivery confirmation).

2. Familiarity with high-performance distributed storage solutions: TiDB CockroachDB or HBase for managing large-scale logistics data (e.g. historical shipment records GPS tracking logs).

3. Experience with specialized logistics technologies: route optimization algorithms (e.g. OR-Tools) geospatial data processing libraries or integration with carrier APIs (e.g. UPS FedEx DHL).

4. Expertise in cloud cost optimization: designing cost-efficient architectures on AWS/Azure for logistics workloads leveraging spot instances auto-scaling groups and serverless technologies to reduce infrastructure expenses during off-peak periods.

5. Contributions to open-source projects or technical blog posts related to Java backend development architecture optimization or logistics technology solutions.

6. Domain Knowledge (Logistics Industry)

Understanding of core logistics workflows: order management fleet tracking route optimization warehouse management systems (WMS) transportation management systems (TMS) and supply chain visibility.

Familiarity with logistics industry standards: EDI (Electronic Data Interchange) for B2B transactions GPS tracking protocols and compliance requirements for shipment data privacy.

Maersk is committed to a diverse and inclusive workplace and we embrace different styles of thinking. Maersk is an equal opportunities employer and welcomes applicants without regard to race colour gender sex age religion creed national origin ancestry citizenship marital status sexual orientation physical or mental disability medical condition pregnancy or parental leave veteran status gender identity genetic information or any other characteristic protected by applicable law.
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