AI Data Ops Engineer
Skills
About This Role
Overview
We're hiring an
AI Data Ops Engineer
- for a leading Abu Dhabi-based holding group investing heavily in its data and AI capability.
- You'll engineer the pipelines that feed everyday AI assistants and enterprise AI products — and you'll be the technical authority reviewing and signing off vendor-delivered data architectures before they reach production.
- Reports to the AI Solutions Manager.
- What you'll own:
- Engineer batch and stream pipelines using Fabric Data Pipelines / Azure Data Factory, Synapse, or Databricks.
- Implement data quality rules, schema validation, de-duplication, SCD, and reconciliation checks.
- Operationalize lineage, cataloging, and classifications with Microsoft Purview; enforce RBAC and access patterns.
- Automate CI/CD via Azure DevOps or GitHub with environment promotion, infrastructure-as-code (Bicep/Terraform), and secrets management via Key Vault.
- Build feature stores and model-serving data contracts in partnership with MLOps and AI engineering teams.
- Own reliability: alerts, runbooks, on-call rotation, and cost and performance optimization.
- Review and finalize vendor-delivered data pipelines and data architecture for AI projects; ensure compliance with client standards for security, performance, and reliability; approve production readiness.
- Collaborate with delivery partner squads on interface specifications, test data, and delivery checkpoints; support SIT/UAT and production cutover.
- Define and enforce Data Contracts and SLAs per priority dataset (schema, refresh frequency, quality thresholds, reconciliation checks, and consumer expectations).
- Own data incident management: classification, RCA, corrective actions, and prevention of recurring nonconformities.
- Formalize the handshake with AI/ML/DevOps engineers on feature and embedding pipelines, monitoring hooks, and release gates for data-dependent AI deployments.
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