Data Infra Platform Engineer
On-siteSingapore, Singapore
Singapore, SingaporeOn-siteFull TimeEnterprise
Full TimeEnterprise
Job Summary
Build the cloud foundation in Terraform and operate the data platform on Kubernetes, including Apache Iceberg, Kafka, Airflow, and managed databases. Enforce data governance through the Polaris catalog and metadata layer, while designing interfaces for team self-service provisioning of resources. Own platform reliability at runtime by defining SLIs and SLOs, managing incident response, and executing safe upgrades with zero data loss. This role supports Thales' global mission in aerospace, cybersecurity, and digital identity by delivering secure, scalable infrastructure that empowers critical decision-making.
Required Qualifications
- Bachelor's degree in computer science, Information Technology or related field
- Masters degree in Computer Science or Information Technology if applicable
- Several years building platform or data-platform capabilities end to end, production-grade, self-service solutions (three to five years is a useful guide)
- Strong, hands-on production of Kubernetes, including operating stateful, distributed systems (databases, brokers, query engines) and resolving issues under pressure
- Hands-on experience operating at least one core data system (Kafka, Iceberg/Trino/Spark, or Airflow) as a platform service
- Experience running data exploration and visualization tooling such as Grafana, Apache Superset, Elasticsearch, and Kibana
- Solid infrastructure-as-code (Terraform or OpenTofu) and GitOps delivery (FluxCD or Argo CD)
- A working command of CI/CD pipelines and release strategy (GitLab, or equivalent)
- A sound grasp of cloud-native security: least privilege, network segmentation, secrets management, identity, and supply-chain integrity
- Operational maturity: defining SLOs, incident response, and safe upgrades with no data loss
- Proficiency in Python and one of Go or Bash, and comfort on Linux
- The conviction that infrastructure is code: version-controlled, reviewed, tested, and secured
- Location: Singapore, Singapore
Desired Qualifications
- A working understanding of how these systems are used
- Working knowledge of SQL and data modelling
- Depth in Azure services (AKS, ADLS Gen2, AI Foundry, Key Vault, Entra ID, Private Endpoints)
- Kafka and Strimzi, including topics, schema, and credential management
- Lakehouse and query engines: Iceberg, Polaris, Trino, and Spark on object storage
- Airflow, including providers and connection management
- Metadata and governance: DataHub, lineage, classification, and catalog RBAC
- Managed databases on Kubernetes (CloudNativePG or similar)
- Building or operating an internal developer or data platform
- You see systems end to end and resist thinking in silos
- You treat the platform as a product: you measure adoption and let evidence, not assumption, guide what to build, harden, or retire
- You have learning agility, flexibility, and initiative
- You are comfortable in an agile team, engaging directly with the developers you serve
- You hold your convictions with humility, welcome feedback, and stay resilient
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