Data Software Engineer

Summary

Catena Clearing is a startup focused on providing a universal API for fleet telematics data. They are seeking a Data Software Engineer to build and maintain data pipelines that integrate various telematics providers into a coherent data product, ensuring high data quality and operational efficiency.

Responsibilities

• Build and operate ingestion pipelines across our telematics provider integrations, streaming, polling, and batch - with the retry, rate-limiting, and backpressure behavior each provider demands
• Own the normalization layer: map wildly inconsistent provider payloads into Catena's canonical vehicle, driver, HOS, and fuel models, and defend that schema as new providers are added
• Design storage and query patterns for high-volume time-series vehicle data, balancing real-time API latency against analytical workloads
• Ship customer-facing data products, stop and geofence detection, ETA computation, location aggregates, IFTA-grade mileage - from spec through production
• Build and maintain write-back workflows that push fuel transactions, DVIR status, and dispatch data back into provider systems, with idempotency and loop protection
• Instrument everything: data freshness, field completeness, provider health, and drift detection, so we catch a broken upstream before a customer does
• Own data quality end to end. In our business a silently wrong location is worse than a missing one - a fuel-card issuer declines a real transaction, an insurer misprices a carrier
• Work directly with customers' engineering teams when the data question is theirs, not ours

Skills

• 3+ years building production data pipelines or backend data services
• Strong Python; comfortable owning services end to end, not just notebooks or DAGs
• Solid SQL and relational data modeling: you can reason about partitioning, indexing, and query cost, not just correctness
• Experience with streaming or event-driven ingestion, and with the operational reality of unreliable third-party APIs
• Cloud-native on AWS
• You've debugged a pipeline that was quietly producing wrong data, and you have opinions about how to prevent it happening again
• Clear written communication, we're remote and async by default
• Experience in telematics, IoT, logistics, fintech, or insurance data - anywhere the data has physical-world ground truth and someone makes a money decision on it
• Time-series or geospatial data at scale: geofencing, map matching, trip and stop inference, H3 or similar indexing
• Data-sharing and multi-tenant delivery patterns - Snowflake shares, per-tenant credential isolation, consent-scoped access
• Experience building against many third-party APIs at once, where you control neither the schema nor the uptime
• Working in a SOC 2 environment, or helping get a company there

Qualifications

Must Haves

• 3+ years building production data pipelines or backend data services
• Strong Python; comfortable owning services end to end, not just notebooks or DAGs
• Solid SQL and relational data modeling: you can reason about partitioning, indexing, and query cost, not just correctness
• Experience with streaming or event-driven ingestion, and with the operational reality of unreliable third-party APIs
• Cloud-native on AWS
• You've debugged a pipeline that was quietly producing wrong data, and you have opinions about how to prevent it happening again
• Clear written communication, we're remote and async by default

Nice to Haves

• Experience in telematics, IoT, logistics, fintech, or insurance data - anywhere the data has physical-world ground truth and someone makes a money decision on it
• Time-series or geospatial data at scale: geofencing, map matching, trip and stop inference, H3 or similar indexing
• Data-sharing and multi-tenant delivery patterns - Snowflake shares, per-tenant credential isolation, consent-scoped access
• Experience building against many third-party APIs at once, where you control neither the schema nor the uptime
• Working in a SOC 2 environment, or helping get a company there

Benefits

• Full benefits
• Equity
• 401k match
• Remote-friendly environment
• Occasional travel for team and customer on-sites