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 such as Terraform.
Experience working with production data access controls and security.
Bachelor’s degree in Computer Science, Engineering, or a related discipline, or equivalent practical experience.
Bachelor’s degree in Computer Science, Engineering, or a related discipline; a Master’s in a related field is preferred, or equivalent practical experience.
Other Qualification
Data Platform
Hands-on experience building or operating multi-team data/lakehouse platforms.
Experience with reusable platform patterns across project structure, orchestration, catalog, CI/CD, and environments.
dbt & Data Products
Strong production dbt experience, including project architecture, macros, packages, tests, and large model graphs.
Experience with data modeling, marts, data quality, and semantic/metrics definitions across multiple domains.
Lakehouse & Query Engines
Strong Trino experience, including query execution and performance tuning.
Hands-on Apache Iceberg experience: partitioning, schema evolution, snapshots, and table maintenance.
Experience with S3 Tables, Glue Catalog, or comparable lakehouse storage/catalog technologies.
Strong understanding of query and data-layout optimization for high-volume workloads.
Visualization
Experience with Apache Superset, Metabase, or similar BI platforms.
Security, Infrastructure & Operations
Experience with Terraform, IAM, least privilege, encryption, CI/CD, monitoring, and production operations.
Experience operating reliable, multi-tenant data platforms.
Kafka, Spark, Flink, or similar distributed technologies are a plus.
Workday Pay Transparency Statement
The annualized base salary ranges for the primary location and any additional locations are listed below. Workday pay ranges vary based on work location. As a part of the total compensation package, this role may be eligible for the Workday Bonus Plan or a role-specific commission/bonus, as well as annual refresh stock grants. Recruiters can share more detail during the hiring process. Each candidate’s compensation offer will be based on multiple factors including, but not limited to, geography, experience, skills, job duties, and business need, among other things. For more information regarding Workday’s comprehensive benefits, please click here.
Primary Location: USA.CA.Pleasanton
Primary Location Base Pay Range: $190,100 USD - $285,100 USD
Additional US Location(s) Base Pay Range: $160,100 USD - $285,100 USD
Our Approach to Flexible Work
With Flex Work, we’re combining the best of both worlds: in-person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. We know that flexibility can take shape in many ways, so rather than a number of required days in-office each week, we simply spend at least half (50%) of our time each quarter in the office or in the field with our customers, prospects, and partners (depending on role). This means you'll have the freedom to create a flexible schedule that caters to your business, team, and personal needs, while being intentional to make the most of time spent together. Those in our remote "home office" roles also have the opportunity to come together in our offices for important moments that matter.
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Workday is an Equal Opportunity Employer including individuals with disabilities and protected veterans.
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