Senior Data Platform Engineer

Ethereum Technologies LLC; Sunnyvale (CA); On-site; USD 150,000 - 190,000; Full time

Job summary

Ethereum Technologies is looking for a data platform engineer to design, deploy, and operate data services on Kubernetes within Microsoft Azure. The role focuses on building lakehouse infrastructure backed by Apache Iceberg with ADLS, configuring catalogs, and managing partitions.

You will run Trino and Spark clusters, develop DBT pipelines, and enforce governance across multi-tenant environments. Responsibilities include observability, incident response, and collaborating with data teams to

Qualifications

• Strong hands-on experience with Kubernetes and stateful workloads.
• Proficiency in Microsoft Azure Cloud and ADLS.
• Experience with Apache Iceberg and catalogs REST.
• Expertise with Trino and Spark for distributed compute.
• DBT data transformations with solid modeling and testing.

Responsibilities

• Design, deploy, and operate data platform services on Kubernetes in Azure.
• Build lakehouse infra on Iceberg backed by ADLS, including catalog setup and partitioning.
• Operate and tune Trino and Spark clusters for performance and cost.
• Develop data transformation pipelines using DBT with tests and docs.
• Define data access, security, governance, and multi-tenant management.
• Implement observability: monitoring, alerts, capacity planning, incident response.
• Collaborate with data engineers, analysts, and platform teams to onboard workloads.
• Automate infra and deployments using IaC and CI/CD.

Skills

Kubernetes

Azure Cloud

Trino

Spark

DBT

Iceberg

Tools

Iceberg catalogs REST

ADLS

Parquet/ORC

Job description

US Citizen, Green Card, H-1B, OPT-EAD, CPT, Other

• Design, deploy, and operate data platform services on Kubernetes in Microsoft Azure.
• Build and manage lakehouse infrastructure on Apache Iceberg backed by ADLS, including catalog configuration, table maintenance, schema evolution, and partitioning strategy.
• Operate and tune Trino and Spark clusters for performance, reliability, and cost efficiency.
• Develop and maintain data transformation pipelines using DBT, with sound modeling, testing, and documentation practices.
• Define and enforce standards for data access, security, governance, and multi-tenant resource management across ADLS and query engines.
• 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.

Required Qualifications

• 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.

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.