Data Ops Engineer

Overview

Data Ops Engineer – Data & AI Platforms at One New Zealand.

Ko Tō Mahi – What You’ll Do

• Define SLIs / SLOs for data freshness, completeness, timeliness, and pipeline success. Build dashboards, alerts, and traces, and ensure every material change includes readiness gate evidence.
• Set and automate acceptance criteria for production and support readiness across security, privacy, observability, and FinOps. Ensure changes are small, reversible, and well-documented.
• Align support structures, on-call coverage, escalation paths, and playbooks with Service Management and partners for BAU and after-hours operations. Maintain current and usable runbooks.
• Enforce tagging to surface product-level costs, monitor budget variances and anomalies, and drive safe optimisations such as caching, batching, and model sizing.
• Collaborate with AIOps on feature and embedding stores, retrieval / RAG patterns, and schema design. Ensure SLAs, caching, and data structures support reliability, safety, and cost goals.
• Maintain up-to-date standards, diagrams, evaluation reports, and runbooks to ensure clean handovers and reduce single points of failure.

Nā Mātou Te Rourou – What You’ll Bring

Na Rourou – What You’ll Get

Joining our whānau is more than starting a new job - it’s the beginning of a journey that will challenge and inspire you to play a role in something bigger.

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