Staff Engineer - Data platform
Kpler · Hybrid
MeritLog read this listing from Kpler's Lever job board and last checked it on September 12, 2026.
Source: the employer's Lever job board. Open the original listing for current details.
Job details
- Work model
- Hybrid
- Salary
- Not listed by source
- Location
- United Kingdom; Greece
- Company website
- www.kpler.com
Hiring context
How this role compares at Kpler
Kpler has 68 live roles in MeritLog’s catalog across 8 job families, and 21 of them are in data & analytics. 5 of those listings publish a pay range, a disclosure rate of 7%.
Kpler concentrates this hiring in:
Counted across the job boards MeritLog tracks, at the time this page was served. Pay comparisons use only listings that publish a complete range in the same currency and period.
Job description
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. The Data platform tribe builds the tooling and foundational datasets that underpin the rest of Kplers products. They drive the development of large-scale, distributed, real-time pipelines for geospatial data using tools like Flink and Iceberg. As a Staff engineer you will be part of the engineering leadership within Kpler, responsible for aligning priorities and ensuring the delivery of key initiatives across team and department boundaries. You will be responsible for raising the bar on the operational maturity of our pipelines while overseeing and defining Kpler’s data architecture.
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