Data Engineer

At Kpler, we are dedicated to helping our clients navigate complex markets with ease. By simplifying global trade information and providing valuable insights, we empower organisations to make informed decisions in commodities, energy, and maritime sectors.

Since our founding in 2014, we have focused on delivering top‑tier intelligence through user‑friendly platforms. Our team of over 700 experts from 35+ countries works tirelessly to transform intricate data into actionable strategies, ensuring our clients stay ahead in a dynamic market landscape. Join us to leverage cutting‑edge innovation for impactful results and experience unparalleled support on your journey to success.

Build and maintain Kpler's core datasets (vessels characteristics, companies, geospatial data).

You will be responsible for creating and maintaining REST APIs, streaming pipelines (Kafka Stream), and Spark batch pipelines.

The role involves end‑to‑end ownership of development tasks, beginning with a thorough understanding of assigned tickets and requirements. The individual designs and builds functionality—including APIs and data processing components—ensuring code is deployed to development environments and reviewed through peer and product testing.

They are responsible for writing and executing unit, integration, and functional tests aligned with defined test scenarios, while ensuring full compliance through detailed validation. After release, the role includes monitoring system performance, alerts, and SLOs to ensure optimal functionality and reliability.

• Deliver well‑documented, maintainable code following Test‑Driven Development (TDD) principles, ensuring comprehensive unit, integration, and end‑to‑end testing.
• Design, operate, and document versioned RESTful APIs using FastAPI and JVM‑based frameworks, ensuring scalability, reliability, and backward compatibility.
• Implement and enforce data schema evolution and versioning strategies to support reliable data exchange across systems.
• Develop and maintain batch and streaming data pipelines using technologies such as Kafka and Spark, handling back pressure, orchestration, retries, and data quality controls.
• Instrument services with metrics, logs, and traces; contribute to CI/CD pipelines, automated testing, and participate in incident response to ensure system resilience and SLO adherence.
• Partner closely with Product and cross‑functional teams to translate requirements into high‑quality technical solutions that deliver business outcomes.
• Adhere to clean code and architectural standards through code reviews, testing, and Agile development practices, ensuring maintainable and compliant solutions.

• 3–5 years of experience in data‑focused software engineering roles.
• Good programming skills in Scala (or JVM) experience with Python preferred.
• Proven experience designing and operating RESTful APIs, versioned interfaces.
• Good understanding of data modeling, schema evolution, and serialization technologies such as Avro or Protobuf.
• Experience building and maintaining batch or streaming data systems, with knowledge of streaming patterns and reliability concerns.
• Familiarity CI/CD pipelines, and modern monitoring and alerting practices.
• Proficiency with Git‑based workflows, code reviews, and Agile development methodologies.
• Good sense of ownership, with pragmatic problem‑solving skills, constructive critique and the ability to deliver end‑to‑end solutions.
• Excellent communication skills and fluency in English, with the ability to collaborate across product and engineering teams.

• Experience with Apache Airflow for workflow orchestration.
• Exposure to cloud platforms (preferably AWS) and infrastructure as code using Terraform.
• Experience with Docker and Kubernetes in production environments.
• Hands‑on knowledge of Kafka and event‑driven or microservices architectures.
• Familiarity with JVM build and tooling ecosystems such as Gradle or Maven.

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