Backend Engineer

About the Role

As an Engineer II within our Engineering Maritime & Logistics division, you will play a pivotal role in designing, building, and operating high-throughput data processing and API distribution systems. You will take end-to-end ownership of real-time streaming applications, backend services, and reliable pipelines that deliver critical maritime intelligence to global consumers via Kafka, Flink, and Snowflake. By maintaining platform resilience and scaling event-driven architectures, your work directly powers the actionable insights our clients rely on to navigate complex global trade.

Key Responsibilities

Key Responsibilities

Design, build, and maintain high-performance backend microservices and APIs using Java, Scala, and Python.

Design, develop, and operate real-time data pipelines and stream-processing applications using Java, Scala, Kafka Streams, and Apache Flink, as well as batch-processing workflows using Python and Apache Airflow.

Drive end-to-end technical ownership of backend services from initial design and testing through deployment, continuous monitoring, and production operations.

Optimize system health, throughput, and consumer lag across streaming infrastructure to maximize data freshness and platform uptime.

Investigate production incidents, perform thorough root-cause analysis, and implement long-term structural improvements.

Reduce technical debt by continuously elevating software maintainability, observability, automated test coverage, and CI/CD practices.

Partner cross-functionally with product managers, platform engineers, and peer teams to turn complex maritime domain needs into robust software.

Experience & Background

What you'll need (Must-haves)

3+ years of professional software engineering experience delivering backend microservices and data pipelines in production.

Strong proficiency and hands-on expertise in Java, Scala, and Python.

Practical experience building and operating event-driven applications or data pipelines in cloud environments (AWS).

Direct experience operating containerized services on Kubernetes and delivering changes using Docker and GitOps workflows.

Solid background in SQL, relational database design, data modeling, and distributed system fundamentals.

Nice-to-haves

Familiarity with geospatial and location-based datasets, including their structures and common use cases. Hands-on experience with geospatial technologies and tools such as GeoServer, PostGIS, WKT, S2, or H3.

Exposure to Test-Driven Development (TDD) and modern observability stacks (Datadog, OpenTelemetry, metrics, tracing).

Experience working on high-throughput, low-latency streaming systems where data freshness is critical.