Senior Data Platform Engineer

Artifintech; Sunnyvale (CA); On-site; USD 150,000 - 230,000; Full time

Job summary

Artifintech in Sunnyvale, CA, seeks a data platform engineer to design, deploy, and operate scalable data services on Kubernetes in Azure. You will build lakehouse infrastructure on Apache Iceberg backed by ADLS and optimize queries with Trino and Spark.

You will implement DBT pipelines, enforce data governance, and establish observability, security, and cost controls while collaborating with platform teams to onboard workloads and automate deployments via IaC and CI/CD.

Qualifications

• Hands-on experience with Kubernetes deployments and operations.
• Hands-on experience with Microsoft Azure Cloud, including ADLS.
• Experience with Apache Iceberg and Iceberg catalogs REST.
• Expertise with Trino and Spark for distributed query/compute.
• Hands-on with DBT for data transformation and analytics engineering.
• Solid understanding of data lake and lakehouse architectures and file formats.

Responsibilities

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

Skills

Kubernetes

Azure Cloud

Data lake concepts

Tools

Apache Iceberg

Trino

Spark

DBT

ADLS

Parquet/ORC formats

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.