Principal Data Engineer (AI Infrastructure)

Location: Sydney, New South Wales, Australia; Singapore

Company

hirify.global Technologies develops and operates energy-efficient AI infrastructure and the hirify.global AI Cloud GPU platform across Asia Pacific.

What you will do

• Own company-wide data architecture, technology standards, storage topology, and streaming-versus-batch decisions.
• Build and operate real-time and AI data pipelines, storage, transformation, and semantic layers for telemetry, billing, incidents, analytics, and reporting.
• Deploy data components as infrastructure-as-code on self-hosted, bare-metal Kubernetes and own reliability, quality, latency, and storage costs.
• Define data contracts, lineage, access controls, observability, schema enforcement, freshness SLAs, and anomaly detection.
• Extend SOC 2 Type 2 and ISO 27001 controls to the data platform and support enterprise and government customer requirements.
• Lead architecture reviews and RFCs, mentor engineers, and communicate technical decisions to engineering leadership, customers, and partner teams.

Requirements

• Bachelor's degree in computer science or a related technical field.
• 10+ years of experience in data engineering or data architecture, including 5+ years making platform-level decisions.
• Hands-on expertise in ingestion, storage, transformation, semantic layers, observability, governance, and high-cardinality telemetry pipelines.
• Production experience with Apache Kafka, Python, SQL, Apache Spark, Airflow, dbt, Databricks or Snowflake, and open-source platforms such as Trino, ClickHouse, Delta Lake, or Apache Iceberg.
• Experience operating stateful data workloads on self-hosted bare-metal Kubernetes with Helm, including backup, recovery, and incident response.
• Clear and effective written and verbal English communication required; willingness to participate in on-call rotations and occasional overseas travel required.

Nice to have

• Background in AI infrastructure, GPU cloud, high-performance computing, or infrastructure telemetry.
• Experience with industrial IoT and OT telemetry pipelines.
• Experience with vector databases, embeddings, and retrieval pipelines for LLM and AI-agent use cases.

Culture & Benefits

• Full-time role in a diverse and inclusive workplace.
• Work on sustainable AI infrastructure and energy-efficient compute systems.
• Collaborate with engineering, AI, application, enterprise, and government stakeholders.