Principal Distributed Systems Engineer

Workday; United States; On-site; USD 170,000 - 250,000; Full time

Job summary

Workday is seeking a Senior Data Platform Engineer on the Data Platform and Observability Engineering team to own the technical vision for a scalable lakehouse data-product platform. You will design end-to-end architecture and mentor engineers across multiple teams.

You will work with dbt Core, Airflow, Trino, Iceberg, S3 Tables, Glue Catalog, and Terraform to ensure performance, governance, and security for mission-critical data workloads.

Qualifications

• Experience designing and operating large-scale data platforms in production.
• Strong proficiency in SQL and data modeling.
• Experience with dbt, Airflow, and distributed processing.

Responsibilities

• Architect and implement Workday's data-product lakehouse platform end-to-end.
• Mentor engineers and set technical direction across multiple teams.
• Ensure security, governance, and reliability of data products.

Skills

Analytical SQL

Distributed systems

Architecture design

Mentoring

Cross-team leadership

Tools

dbt Core

Airflow

Trino

Apache Iceberg

S3 Tables / AWS Glue Catalog

Terraform

Job description

Your work days are brighter here.

We're obsessed with making hard work pay off, for our people, our customers, and the world around us. As a Fortune 500 company and a leading AI platform for managing people, money, and agents, we're shaping the future of work so teams can reach their potential and focus on what matters most. The minute you join, you'll feel it. Not just in the products we build, but in how we show up for each other. Our culture is rooted in integrity, empathy, and shared enthusiasm. We're in this together, tackling big challenges with bold ideas and genuine care. We look for curious minds and courageous collaborators who bring sun-drenched optimism and drive. Whether you're building smarter solutions, supporting customers, or creating a space where everyone belongs, you'll do meaningful work with Workmates who've got your back. In return, we'll give you the trust to take risks, the tools to grow, the skills to develop and the support of a company invested in you for the long haul. So, if you want to inspire a brighter work day for everyone, including yourself, you've found a match in Workday, and we hope to be a match for you too.

About the Team

The Data Platform and Observability Engineering (DPOE) team is building Workday's next-generation data-product platform the compute, storage, catalog, orchestration, governance, and developer workflows that engineering and analytics teams use to create and operate production data products and marts.

We own the services and infrastructure behind a modern lakehouse stack: dbt Core, Airflow, Trino, Apache Iceberg, Amazon S3 Tables, AWS Glue Catalog, access control, and a visualization layer such as Apache Superset or Metabase. We treat the platform as a product. Our roadmap is how Workday teams model, test, query, and govern high-volume data without each standing up a stack of their own.

About the Role

Own the technical vision and architecture for Workday's data-product platform - a highly scalable lakehouse that lets teams build, govern, and operate data products and marts. This is a hands-on, high-autonomy role for an engineer who can design the platform end-to-end (modeling and dbt, orchestration, distributed query, table format, catalog, security, and infrastructure as code) and who still writes and reviews highly performant analytical SQL.

You will set technical direction across multiple teams, mentor senior and staff engineers, and act as the primary architect and escalation point for the platform - from project and pipeline design through query performance, governance, and reliability.

Architect and build the data-product platform on dbt Core, Airflow, Trino, Apache Iceberg, S3 Tables, and Glue Catalog, designed for high-volume ingestion and interactive query performance.

Own the platform path teams use to ship products: project structure, orchestration, CI/CD, environments, semantic / metrics definitions, and operational support.

Drive performance and scaling across modeling and query paths: Iceberg layout and maintenance, partitioning, incremental processing, compression, and Trino tuning under production load.

Lead HA/DR design for platform services - multi-AZ resilience, failover, backup/restore, and recovery objectives appropriate to a shared production platform.

Design security and access-control architecture, including authentication and authorization for multi-tenant data access across catalog, compute, storage, and visualization.

Use Terraform to define how the platform is built and evolved; set the bar for infrastructure, environments, and blast radius.

Own operational excellence: monitoring, alerting, capacity planning, safe reruns and backfills, and participation in an on-call rotation for the platform.

Evaluate and introduce new technologies , open source and cloud-native and that materially improve scalability, cost efficiency, governance, or developer experience.

Shape how teams use the platform: reusable dbt and modeling patterns, data-quality frameworks, and a visualization layer (Apache Superset, Metabase, or equivalent) connected to governed catalogs and Trino.

Evangelize the platform: publish best practices, mentor engineers across DPOE and partner teams, and act as a technical thought leader for the modern lakehouse and data-product stack internally.

Operate with high autonomy in a fast-moving, ambiguous environment, setting technical direction with minimal oversight while aligning with broader platform strategy.

About You

You have designed and operated large-scale data or distributed systems in production. You still write code. You can start from a blank dbt project and from a blank Terraform stack, and you can explain how Airflow, Trino, Iceberg, the catalog, object storage, and access control share responsibility.

You think about the platform as a product. You care about scalability, reliability, performance, security, operability, and developer experience not just whether an individual query or pipeline works. Yo