Senior Backend Engineer - Commodities

• Design, build, and operate major platform components end-to-end, spanning high-throughput streaming ingestion (Kafka, Airflow, Python/FastAPI) to web applications (TypeScript/Vue).

• Lead subsystem architecture by writing design specifications, conducting peer reviews, and making pragmatic build-versus-adapt decisions.

• Guarantee production operational excellence through rigorous SLO management, comprehensive system observability, on-call rotation, and incident response.

• Architect data quality frameworks—including telemetry validation, reconciliation, and time-series monitoring—to ensure field sensor data is accurate and reliable.

• Collaborate with core marine tracking and data platform teams to seamlessly integrate inland data feeds into Kpler's broader platform architecture.

• Mentor mid-level engineers through technical design guidance, code reviews, and pair programming while setting team-wide engineering conventions.

• Partner directly with early customers (traders, analysts, operations teams) and product leaders to demo features, gather feedback, and shape product roadmaps.

What you'll need (Must-haves)

• 5+ years of professional software engineering experience building and operating distributed production systems.

• Proven experience architecting event-driven or data-intensive systems using streaming technologies like Kafka or similar message queues.

• Strong backend engineering mastery in Python and REST API design (e.g., FastAPI), alongside comfort contributing to frontend surfaces (TypeScript/Vue).

• Direct experience managing production cloud infrastructure (AWS preferred), including SLO establishment, incident management, and deep observability.

• Demonstrated capability to mentor engineers, guide technical discussions, and engage directly with end-users or stakeholders.

Nice-to-haves

• Experience with Scala or running Elasticsearch clusters at scale.

• Hands-on background handling IoT telemetry, remote sensor feeds, time-series data, or geospatial datasets.

• Domain knowledge in energy, oil & gas, or global commodities markets.

• Prior experience as an early or founding engineer in a new product initiative.