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Prepare for this job
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Prepare for this interviewAt a glance
- Experience asked
- 3+ years
- Education
- Master's
Skills mentioned
About the role
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
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Design, build, and maintain high-performance backend microservices and APIs using Java, Scala, and Python.
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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.
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Drive end-to-end technical ownership of backend services from initial design and testing through deployment, continuous monitoring, and production operations.
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Optimize system health, throughput, and consumer lag across streaming infrastructure to maximize data freshness and platform uptime.
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Investigate production incidents, perform thorough root-cause analysis, and implement long-term structural improvements.
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Reduce technical debt by continuously elevating software maintainability, observability, automated test coverage, and CI/CD practices.
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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)
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3+ years of professional software engineering experience delivering backend microservices and data pipelines in production.
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Strong proficiency and hands-on expertise in Java, Scala, and Python.
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Practical experience building and operating event-driven applications or data pipelines in cloud environments (AWS).
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Direct experience operating containerized services on Kubernetes and delivering changes using Docker and GitOps workflows.
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Solid background in SQL, relational database design, data modeling, and distributed system fundamentals.
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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.
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Exposure to Test-Driven Development (TDD) and modern observability stacks (Datadog, OpenTelemetry, metrics, tracing).
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Experience working on high-throughput, low-latency streaming systems where data freshness is critical.
Nice-to-haves
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