kpler - Backend Engineer - Commodities
Requirements
• 2 to 4 years of professional software engineering experience building and supporting production software. • Strong proficiency with Python and relational databases (SQL / Postgres). • Proven experience deploying, debugging, and operating backend services in cloud environments (AWS preferred). • Hands-on exposure to message queues, streaming platforms (e.g., Kafka), and RESTful API development. • Strong problem-solving skills with a high degree of agency to move from ambiguous requirements to working code. • Experience with FastAPI, Airflow, TypeScript, Vue, or Elasticsearch. • Prior exposure to time-series, IoT, remote sensor, or geospatial datasets. • Domain interest in energy, commodities, or logistics supply chains. • We are a dynamic company dedicated to nurturing connections and innovating solutions to tackle market challenges head-on. If you thrive on customer satisfaction and turning ideas into reality, then you’ve found your ideal destination. Are you ready to embark on this exciting journey with us? • We make things happen • We act decisively and with purpose, going the extra mile. • We build together • We foster relationships and develop creative solutions to address market challenges. • We are here to help • We are accessible and supportive to colleagues and clients with a friendly approach. • Our People Pledge • Don’t meet every single requirement? Research shows that women and people of color are less likely than others to apply if they feel like they don’t match 100% of the job requirements. Don’t let the confidence gap stand in your way, we’d love to hear from you! We understand that experience comes in many different forms and are dedicated to adding new perspectives to the team.
Responsibilities
• Build and maintain scalable ingestion and processing pipelines for sensor, rail, and waterway data using Python, Kafka, and Airflow. • Develop backend services using FastAPI and contribute to customer-facing web applications using TypeScript and Vue. • Implement data validation, system monitoring, and alerting to ensure noisy time-series data from field hardware remains accurate and complete. • Operate owned services end-to-end, taking charge of deployments, observability, and participation in the team's on-call rotation. • Collaborate closely with data science and sensor operations teams to transform raw telemetry into high-value, usable datasets for early customer adoption. • Drive continuous platform health by participating in technical design discussions, improving CI/CD workflows, and delivering tested, well-documented code.
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