Backend Engineer

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.

About the Role

As a Senior Software Engineer within our Commodities tribe, you will lead the end-to-end integration of US inland waterway barge data into Kpler’s global cargo intelligence platform. Operating under a "you build it, you run it" philosophy, you will design robust ingestion paths, stream real-time data using Kafka, and connect barge movement models directly to our customer-facing surfaces. This role carries genuine design authority, empowering you to solve complex entity resolution problems while mentoring peers and elevating technical craft across our crews.

Key Responsibilities

Lead end-to-end integration architecture: Drive the full engineering lifecycle—from external feed ingestion and domain modeling to streaming, entity resolution, and UI distribution.

Design robust ingestion & entity-resolution systems: Map incoming barge data onto Kpler reference data (vessels, zones, installations, products) using existing Elasticsearch and PostgreSQL matching patterns.

Build scalable Kafka streaming pipelines: Construct event-driven contracts, schemas (Avro), deduplication mechanisms, and dead-letter queue replays with Python and Scala.

Deliver data across customer surfaces: Surface integrated barge data cleanly across Elasticsearch read models, external APIs, data warehouse feeds, and the Kpler Terminal (TypeScript/Vue).

Champion production quality & observability: Maintain full operational ownership of your services, setting SLOs, participating in on-call rotations, and driving post-incident improvements.

Ensure data integrity & analyst alignment: Validate external feeds and integrate human-in-the-loop analyst workflows so corrections seamlessly apply to barge movements.

Mentor and elevate engineering craft: Guide and mentor crew members, document architectural designs, and actively contribute to decomposing legacy estates into event-driven services.

Experience & Background

• What you'll need (Must-haves)
• Production data engineering experience: ~5+ years of experience designing, operating, and maintaining data-intensive production systems with full ownership.
• Advanced Python & SQL expertise: Proven ability to build clean, well-bounded services within large, complex, and evolving codebases.
• Event-driven streaming proficiency: Hands-on experience with Kafka streaming in production, including schema management (Avro/Schema Registry), deduplication, and replay patterns.
• Third-party integration & entity resolution: Demonstrated background integrating external data feeds, managing schema mapping, and building data quality monitoring frameworks.
• Operational mindset: Direct experience managing production observability, writing documentation, and resolving incidents in a distributed system environment.

Nice-to-haves

• Functional programming & Scala: Experience or familiarity with Scala (Kafka Streams) or a track record of rapidly mastering new languages.
• Geospatial & domain knowledge: Familiarity with geospatial data tools (PostGIS) or exposure to maritime, logistics, or commodities domains.
• Modern data stack exposure: Experience with Elasticsearch, Airflow, Snowflake/lakehouse table formats, Kubernetes, and GitOps deployments.
• UI/Frontend collaboration: Working knowledge of TypeScript or Vue to collaborate on user-facing terminal features.