About Kpler
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.
Responsibilities
•Architect, build, and optimize scalable data pipelines and stream-processing workflows using Python, Apache Spark, Kafka, and Airflow.
•Maintain and evolve data architecture across polyglot backend microservices (Python/FastAPI, PHP, Java/Scala) to support continuous analytics delivery.
•Ensure end-to-end data quality, freshness, and reliability by implementing automated validation, monitoring frameworks, and strict SLA tracking.
•Provision and manage cloud-native data infrastructure on AWS using Terraform, Docker, and automated CI/CD practices.
•Collaborate cross-functionally with Product Managers, SRE, Platform Engineers, and Data Scientists to translate complex domain needs into performant data products.
•Drive operational and cost efficiency across data infrastructure, optimizing cloud resource usage and pipeline performance.
Requirements
•6+ years of professional software or data engineering experience building complex, production-grade data processing systems.
•Strong expertise in Python and hands-on experience with distributed data processing tools such as Apache Spark, Kafka, or Airflow.
•Advanced knowledge of database design, SQL performance tuning, and data modeling across relational and NoSQL stores.
•Proven experience managing cloud infrastructure on AWS, utilizing Terraform, Docker, and modern CI/CD pipelines.
•Practical experience writing clean, maintainable code in polyglot environments (Python, Java/Scala, or PHP).
Nice to have
•Experience building RESTful APIs using Python frameworks like FastAPI.
•Background handling high-throughput time-series, geospatial, or maritime logistics datasets.
•Exposure to cloud FinOps, observability, and cost management tooling (e.g., Datadog, Astronomer).
Conditions
Not specified in the posting.
