Senior Software Engineer(Distributed Systems)

Workday; United States; On-site; USD 150,000 - 210,000; Full time

Job summary

Workday is seeking a hands-on Software Development Engineer to build and operate a scalable data-product platform used by engineering and analytics teams to create and govern production data products and marts. The platform spans dbt Core, Airflow, Trino, Apache Iceberg, Amazon S3 Tables, AWS Glue Catalog, access control, security, infrastructure as code, and CI/CD.

This role combines data platform engineering with hands-on data-product development.

Qualifications

• 8+ years of software engineering or data engineering experience.
• 5+ years of experience building or operating production data platforms, lakehouse platforms, or distributed data systems.
• Hands-on experience building and maintaining production dbt Core projects.
• Strong production SQL and data-modeling experience.
• Experience with Airflow or another production workflow orchestration platform.
• Experience with Trino or another distributed SQL/query engine.
• Experience with a lakehouse technology such as Apache Iceberg, Delta Lake, or Hudi.
• Experience with cloud object storage and metadata/catalog systems.
• Experience with Python, Java, Go, Scala, or another production programming language.
• Experience with infrastructure as code s

Responsibilities

• Build and evolve platform capabilities across dbt, Airflow, Trino, Iceberg/S3 Tables, Glue Catalog, security, and infrastructure.
• Create and maintain production dbt projects end-to-end, including data models, transformations, tests, documentation, and semantic definitions.
• Design and operate Airflow workflows with scheduling, dependencies, retries, backfills, and recovery.
• Develop and optimize high-volume analytical workloads on Trino and Iceberg, including partitioning, incremental processing, file layout, and query performance.
• Implement data quality, access control, and security using governed catalog and IAM patterns.
• Use Terraform and CI/CD to automate platform and data-product deployment.
• Contribute to the semantic and visualization layer for data-product consumption.
• Troubleshoot and operate the full stack, with a focus on reliability, scalability, and safe production operations.
• Build reusable platform patterns that make it easier for teams to develop and operate data products.
• Support and mentor team members on data platform and data-product development.

Skills

SQL & data modeling

Production data platforms

Python/Java/Go/Scala

Distributed data systems

Data governance

Tools

dbt Core

Airflow

Trino

Iceberg

S3/Glue Catalog

Terraform

CI/CD

Job description

About the Team

Data Platform and Observability Engineering builds the platforms Workday teams use to turn data into reliable, governed products. We sit at the intersection of distributed systems, analytics engineering, and platform operations.This team is building a highly scalable data-product platform: compute, storage, catalog, orchestration, access control, and the workflows teams use to develop, test, and operate data products and marts. We treat the platform as a product, reusable capabilities, clear contracts, and a path from model to query to visualization, so engineering and analytics teams can own what they build without each standing up a stack of their own.We work closely with domain engineering, analytics, security, and infrastructure partners. The work is hands-on: production SQL and dbt, lakehouse services, Terraform, and the operational bar for high-volume, multi-team use.

About the Role

We are looking for a hands‑on Software Development Engineer to build and operate a scalable data‑product platform that enables engineering and analytics teams to create and govern production data products and marts.The platform spans the full data‑product lifecycle, including dbt Core, Airflow, Trino, Apache Iceberg, Amazon S3 Tables, AWS Glue Catalog, access control, security, infrastructure as code, and CI/CD.This role combines data platform engineering with hands‑on data‑product development. You will help build the underlying platform and its reusable capabilities, while also creating and maintaining production dbt projects, data models, tests, semantic definitions, and data marts. You will write highly performant analytical SQL, and you will help teams use a visualization layer such as Apache Superset or Metabase.You will work on problems involving high-volume data, distributed query processing, data modeling, data quality, platform reliability, governance, security, and developer experience.

What You Will Do

• Build and evolve platform capabilities across dbt, Airflow, Trino, Iceberg/S3 Tables, Glue Catalog, security, and infrastructure.
• Create and maintain production dbt projects end-to-end, including data models, transformations, tests, documentation, and semantic definitions.
• Design and operate Airflow workflows with scheduling, dependencies, retries, backfills, and recovery.
• Develop and optimize high-volume analytical workloads on Trino and Iceberg, including partitioning, incremental processing, file layout, and query performance.
• Implement data quality, access control, and security using governed catalog and IAM patterns.
• Use Terraform and CI/CD to automate platform and data-product deployment.
• Contribute to the semantic and visualization layer for data-product consumption.
• Troubleshoot and operate the full stack, with a focus on reliability, scalability, and safe production operations.
• Build reusable platform patterns that make it easier for teams to develop and operate data products.
• Support and mentor team members on data platform and data-product development.

About You

Basic Qualification

Basic Qualifications

• 8+ years of software engineering or data engineering experience.
• 5+ years of experience building or operating production data platforms, lakehouse platforms, or distributed data systems.
• Hands‑on experience building and maintaining production dbt Core projects.
• Strong production SQL and data-modeling experience.
• Experience with Airflow or another production workflow orchestration platform.
• Experience with Trino or another distributed SQL/query engine.
• Experience with a lakehouse technology such as Apache Iceberg, Delta Lake, or Hudi.
• Experience with cloud object storage and metadata/catalog systems.
• Experience with Python, Java, Go, Scala, or another production programming language.
• Experience with infrastructure as code s