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 850 experts from 69 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.

Architect and maintain data ingestion pipelines: Design, implement, and operate flexible data ingestion frameworks using Java (sourcing from Kafka, S3, and Iceberg) and Python with Airflow to power analytical platforms like Snowflake and ClickHouse . Drive operational excellence and reliability: Maintain end-to-end service ownership by setting up proactive monitoring, establishing actionable alerts, reducing pipeline failure modes, and participating in on-call readiness . Lead technical project delivery: Break down complex engineering problems, author clear design proposals, and lead peer engineers to ship capabilities end-to-end on schedule . Elevate developer experience and platform standards: Build reusable tools, clear documentation, and paved paths that enable adjacent engineering crews to adopt and extend data ingestion frameworks with minimal friction . Partner across engineering and client stakeholders: Collaborate with Cloud Platform engineers, Product Managers, tech leads, and technical teams at clients to align pipeline capabilities with broader business and customer needs . Mentor and grow the engineering crew: Onboard new engineers, conduct constructive code reviews, and share technical best practices to foster continuous improvement across the team .

What you'll need (Must-haves) Data ingestion & engineering experience: ~3+ years of professional software or data engineering experience building, operating, and maintaining production data ingestion pipelines (batch/streaming) using tools like Kafka, S3, Iceberg, or Airflow . Core programming & data stack depth: High proficiency in Java and Python, backed by strong SQL skills, data modeling fundamentals, and analytical warehouse experience (Snowflake or equivalent cloud data warehouse) . Production & DevOps mindset: Demonstrated ownership of production cloud services on AWS, including monitoring/observability, performance tuning, and Kubernetes deployment workflows (GitOps/CI/CD) . Collaborative communication: Strong communication skills to partner with cross-functional product, platform, and external client technical teams . Nice-to-haves Snowflake & ClickHouse optimization: Hands-on experience optimizing Snowflake resource sizing and cost/performance trade-offs, or operating OLAP engines like ClickHouse . Client delivery patterns: Familiarity with AWS Transfer Family (sFTP), Excel add-in integrations, or Python boto3 client data delivery setups . Frontend awareness: Basic exposure to TypeScript, Vue.js, or API integrations for presenting data in end-user workflows .

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