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Kpler

Posted 3 months ago

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Data Engineer - Dry Bulk Commodities

GermanyRemoteFull-time

AI Summary

Data Engineer in the Dry Bulk market data operations team builds tools and pipelines to maintain cargo-tracking data quality at scale, bridging analytics and engineering.

About this role

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.


Your future position
Kpler provides the most comprehensive tracking of commodity flows in dry bulk, and we are rapidly expanding our coverage. As a Data Engineer within our Dry Bulk market data operations team, you'll build the tools and analytical capabilities that enable our analysts to maintain the integrity of our cargo tracking data at scale. This role will bridge the gap between market analytics and engineering, developing tools and systems that make surgical data interventions more efficient and scalable.

Your mission is to:

  • Create scripts, CLI utilities, and web-based UIs (using tools like Streamlit) that empower analysts to perform data quality interventions more efficiently and at greater scale
  • Query and analyse substantial datasets to surface insights, identify data quality issues, and inform both tactical interventions and strategic improvements
  • Work alongside software engineers to develop backend tools and data pipelines that improve the overall quality and reliability of our tracking systems
  • Understand the day-to-day challenges analysts face and translate those pain points into technical solutions that reduce manual effort
  • Create clear documentation for tools, data processes, and analytical approaches to ensure knowledge sharing across the team
  • Develop automated checks and monitoring systems that proactively flag data anomalies before they require manual intervention
  • Rapidly test new approaches to data quality challenges, learning from what works and what doesn't, and scaling successful solutions
  • This could be a match if you have/are:

  • Experience extracting, transforming and analysing data from databases and APIs
  • Comfortability working with large, unstructured datasets too complex for standard spreadsheet tools
  • Experience tackling problems that have required learning new tools or technical approaches
  • Background working as part of a multidisciplinary team, particularly with mixed technical/non-technical colleagues
  • Proficiency in Python (or demonstrable ability to become proficient quickly)
  • Experience building CLI tools, or scripts that automate processes and improve team efficiency
  • Familiarity with Git-based workflows and code reviews
  • A mindset that prioritises delivering practical, workable solutions over chasing perfect ones that never ship
  • The inclination to take ownership of problems, using initiative to tackle issues, without waiting to be asked
  • Skills

    APIsAutomationCLI ScriptingCLI ToolsData AnalysisDatabasesData PipelinesData Quality ChecksDocumentationGitMonitoringPandasPythonScalabilitySQLStreamlitUnstructured DataWeb-based UI

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