Senior Data Platform Engineer

Machine Learning Technologies, LLC; Sunnyvale (CA); On-site; USD 190,000 - 250,000; Full time

Job summary

Machine Learning Technologies, LLC is seeking a Data Platform Engineer in Sunnyvale, CA to design, deploy, and operate data platform services on Kubernetes in Microsoft Azure. The role builds lakehouse infrastructure on Apache Iceberg backed by ADLS and tunes Trino and Spark clusters for performance and cost efficiency.

The ideal candidate will develop DBT pipelines, enforce governance across ADLS and query engines, and implement observability with monitoring and incident response.

Qualifications

• Hands-on experience deploying and operating Kubernetes stateful and distributed workloads.
• Experience with Azure Cloud and ADLS.
• Hands-on with Apache Iceberg and catalogs REST.
• Expertise with Trino and Spark for distributed compute.
• DBT for data transformation and analytics engineering.
• Solid understanding of lakehouse architectures and file formats (Parquet/ORC).

Responsibilities

• 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 and partitioning strategy.
• Operate and tune Trino and Spark clusters for performance and cost efficiency.
• Develop and maintain data transformation pipelines using DBT with solid modeling, testing, and documentation.
• Define and enforce data access, security, governance, and multi-tenant resource management across ADLS and query engines.
• Implement observability for the platform with monitoring, alerting, capacity planning and incident response.
• Collaborate 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.

Skills

Distributed data platform knowledge

Cross-team collaboration

Tools

Kubernetes

Microsoft Azure Cloud

ADLS

Apache Iceberg

Iceberg catalogs REST

Trino

Spark

DBT

Parquet

ORC

Job description

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.