Principal Data Engineer (AI Infrastructure)

Location: Singapore

Company

hirify.global Technologies develops and operates energy-efficient AI infrastructure and hirify.global AI Cloud, a GPU cloud platform for training and deploying AI models.

What you will do

• Own the company-wide data architecture, technology strategy, design patterns, and engineering standards.
• Build and operate real-time and batch data pipelines for GPU telemetry, cooling sensors, billing, incidents, and AI workflows.
• Design storage, transformation, semantic, and data lake layers for BI, analytics, and customer-facing reporting.
• Define data contracts, lineage, access controls, quality standards, freshness SLAs, and anomaly detection practices.
• Extend SOC 2 Type 2 and ISO 27001 controls to the data platform and support enterprise and government compliance needs.
• Lead architecture reviews, RFCs, technical decisions, mentoring, stakeholder discussions, and customer-facing architecture conversations.

Requirements

• 10+ years of experience in data engineering or data architecture, including 5+ years making platform-level decisions.
• Hands-on expertise across ingestion, storage, transformation, semantic layers, observability, governance, and high-cardinality telemetry pipelines.
• Experience with Apache Kafka, Python, SQL, Apache Spark, Airflow, dbt, Databricks or Snowflake, Spark, Trino, ClickHouse, Delta Lake, or Apache Iceberg.
• Experience operating stateful data workloads with Helm and self-hosted, bare-metal Kubernetes.
• Experience delivering data governance programs aligned with SOC 2 Type 2 or ISO 27001.
• Clear and effective written and verbal English communication is required. Willingness to participate in on-call rotations and travel overseas occasionally is also required.

Nice to have

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

Culture & Benefits

• Work on sustainable AI infrastructure and energy-efficient GPU computing.
• Contribute to a diverse and inclusive workplace.
• Collaborate with engineering, AI, application, platform, enterprise, and government stakeholders.
• Join a full-time engineering role based in Singapore.