Senior Analytics Engineer

Job description

Job responsibilities

• Own end-to-end analytics products: define success metrics, design schemas, implement ETL/ELT pipelines, test for accuracy, and operate datasets in production.
• Deliver the first 6-month roadmap items as DRI (examples): consolidate multi-source aircraft availability signals into a single fleet health data set;
• Implement rigorous validation: automated data-quality checks, anomaly detection, and rollback procedures with measurable alert thresholds and agreed remediation SLAs with ops owners.
• Build semantic layers, governed metrics, and documented data contracts consumed by BI and AI tools; enforce backward-compatibility and versioning so downstream consumers do not break.
• Partner closely with the Software, Hardware, Field Ops, and Manufacturing to fix upstream data quality issues at the source;
• Instrument and measure impact: define and report KPIs such as data-accuracy error rate, pipeline MTTR, consumer adoption, reduction in manual reconciliation time, and operational decisions enabled (e.g., % improvement…
• Extend Zipline’s internal AI analytics harness: add evaluation tests, ground-truth datasets, and conservative fallback behaviors to ensure AI answers used in ops are explainable and auditable.
• Mentor and elevate the team: set standards for testing, dbt CI/CD, production monitoring, and runbooks; onboard and review work from junior analytics engineers.