Senior Full Stack Software Engineer, Data

Responsibilities: Own end-to-end analytics products: define success metrics, design schemas, implement ETL/ELT pipelines, and operate datasets in production Deliver the first 6-month roadmap items as DRI, e.g., consolidated fleet health data set and governed delivery-performance metrics Implement rigorous data quality checks, anomaly detection, and rollback procedures with predefined SLAs Build semantic layers, governed metrics, and data contracts consumed by BI and AI tools with versioning Collaborate with Software, Hardware, Field Ops, and Manufacturing to fix upstream data quality issues and coordinate schema changes Instrument and measure impact via KPIs such as data accuracy, MTTR, and on-time deliveries influenced by analytics Extend Zipline’s AI analytics harness with tests and explainable, auditable AI outputs used in ops Mentor the analytics team by setting testing standards, CI/CD for dbt, production monitoring, and runbooks

Key requirements: 7+ years in analytics engineering, data engineering, or software engineering with ownership of production systems Proven incident response experience and durable fixes in production environments Deep SQL expertise with Snowflake and dbt, including model versioning and deployments Production Python for EL pipelines, validation, and automation; familiarity with Airflow or similar Experience building semantic layers and governed metrics, with data contracts and SLAs Experience operating under strict correctness and latency SLAs in regulated environments (logistics, manufacturing, aviation) Strong data quality, anomaly detection, and incident response runbooks with measurable improvements Comfort with cross-team decision making and engineering tradeoffs (cost vs. latency vs. reliability) Bachelor’s degree in a quantitative field or equivalent experience Cross-functional collaboration Proactive problem-solving Strong communication SQL (deep expertise) Snowflake dbt