Software Engineer, Data Platform

Responsibilities

• Design, implement, and maintain high-throughput data pipelines for kHz-class, high-channel-count sensor telemetry.
• Design and operate time-series storage and industrial data historians for retention, query performance, and schema evolution.
• Build ingestion and streaming services with buffering, backpressure, idempotency, and no silent data loss.
• Define and promote software engineering practices, data architecture, schema standards, testing strategies, and operational best practices.
• Collaborate with controls, test automation, and visualization teams to support downstream analytics and live dashboards.
• Lead debugging, root cause analysis, and reliability improvements across the ingestion-to-storage stack.
• Set engineering standards and build and mentor high-performance engineering teams.

Requirements

• Bachelor’s degree or higher in Computer Science, Computer Engineering, Software Engineering, or a related field.
• At least 5 years of experience building data pipelines, streaming systems, or backend data infrastructure.
• Strong production-level experience with Python and SQL.
• Hands-on experience with high-throughput data ingestion and time-series or historian storage.
• Strong understanding of distributed systems and data reliability.
• Experience with high-reliability, on-premise, 24/7 deployments in safety-critical environments.
• Preferred experience with InfluxDB, TimescaleDB, Redis, OT/industrial data historians, MQTT, DDS, OPC-UA, Kafka, observability, infrastructure-as-code, and Grafana.
• Preferred background in industrial automation, aerospace, energy, finance/trading, telecom, or scientific research.
• Ability to work extended hours and weekends as necessary.

Benefits

• Base salary range of $125,000–$220,000 annually.
• Full-time hires may be eligible for long-term incentives in the form of stock options.
• Access to medical, vision, and dental coverage.
• Access to a 401(k) retirement plan.