About the Role
As a Full Stack Engineer within our Maritime & Logistics division, you will design, build, and operate systems that power Kpler’s core maritime distribution channels, including our APIs, Snowflake datastores, and real-time Kafka streams. Taking full end-to-end ownership of backend services and streaming pipelines, you will turn complex technical designs into resilient, production-grade applications. Your work ensures maritime data is processed efficiently, made available reliably, and delivered with the performance required by global industry leaders. Collaborating across engineering, product, and platform teams, you will directly drive the evolution and scalability of Kpler's maritime platform.
Key Responsibilities
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End-to-End Service Ownership: Own backend services, streaming applications, APIs, and data pipelines from technical design and implementation through deployment, monitoring, and production operation.
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Stream & Pipeline Engineering: Build and evolve real-time stream processing applications using Java, Scala, Apache Kafka Streams, or Apache Flink to process data with high performance.
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API Development: Design, build, and maintain scalable APIs using TypeScript, Java, and PHP to expose maritime data to internal and external consumers.
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Datastore Integration: Develop reliable data pipelines that consume data from Kafka topics and persist it into target datastores like Snowflake.
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System Observability: Monitor the health, throughput, consumer lag, and error rates of Kafka-based systems to ensure reliable data delivery.
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Incident Management: Investigate production issues, participate in root cause analyses, and implement preventive measures to systematically improve system resilience.
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Technical Quality & Mentorship: Drive code reviews, share technical knowledge, reduce technical debt, and mentor junior engineers.
Experience & Background
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Core Backend Engineering: 3 to 6 years of professional engineering experience designing, building, and maintaining APIs and backend microservices using languages such as Java, TypeScript, PHP, or Scala.
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Data Pipelines & Event Streaming: Demonstrated experience building and operating data pipelines or stream-processing applications in production environments.
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Production Systems Operations: Hands-on experience operating production systems, including monitoring, troubleshooting, performance analysis, and incident investigation.
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Cloud & Operations: Working knowledge of AWS (e.g., IAM, S3) and experience running containerized services in Kubernetes via GitOps-style workflows.
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Education & Methodologies: Bachelor's degree (or equivalent professional experience) in Computer Science or Software Engineering, with strong Agile collaboration skills and fluent English communication.
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Streaming Frameworks: Hands-on experience with Apache Flink, Kafka Streams, or building pipelines that consume Kafka topics and persist data across datastores.
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Quality & Observability Practice: Familiarity with Test-Driven Development (TDD) and improving distributed system observability using metrics, logging, tracing, and alerting.