Jobs → Data & Analytics → Data Platform Engineer

About the Role We are seeking a Data Platform Engineer to design, deploy, and operate data platform services on Kubernetes in Microsoft Azure. This role involves building and managing lakehouse infrastructure and developing data transformation pipelines. Key Responsibilities • Design, deploy, and operate data platform services on Kubernetes in Microsoft Azure • Build and manage lakehouse infrastructure on Apache Iceberg backed by ADLS • Operate and tune Trino and Spark clusters for performance, reliability, and cost efficiency • Develop and maintain data transformation pipelines using DBT • Define and enforce standards for data access, security, governance, and multi-tenant resource management • Implement observability for the platform, including monitoring, alerting, capacity planning, and incident response • Partner with data engineers, analysts, and platform teams to onboard workloads and resolve performance bottlenecks • Automate infrastructure and deployments using infrastructure-as-code and CI/CD Requirements • 15+ years of experience in data platform engineering • Strong hands-on experience with Kubernetes, including deploying and operating stateful and distributed workloads • Strong hands-on experience with Microsoft Azure Cloud, including ADLS • Hands-on experience with Apache Iceberg and Iceberg catalogs REST • Expertise in distributed query and compute technologies, specifically Trino and Spark • Hands-on experience with DBT for data transformation and analytics engineering • Solid understanding of data lake and lakehouse architectures, file formats (Parquet, ORC), and query optimization