The opportunity
At Gusto, we're on a mission to grow the small business economy. We handle the hard stuff — payroll, health insurance, 401(k)s, and HR — so owners can focus on their craft and their customers.
What you'll do
+ years of industry experience in data engineering building scalable data pipelines and data products
Strong proficiency in SQL and at least one programming language (e.g., Python, Scala, or Java)
Proven experience building and maintaining robust data pipelines and ETL: workflows, with hands-on dbt experience for reliable, testable, and maintainable data transformations.
Hands-on experience ingesting data from diverse sources, including APIs,: databases, SaaS applications, and event streams.
Strong foundation in data modeling, schema design, and data quality best: practices, with functional experience working on cloud platforms like Snowflake, Redshift, BigQuery, or Databricks.
Experience implementing CI/CD pipelines, automated testing, and data: observability to ensure reliability and trust in data systems
What they're looking for
- + years of industry experience in data engineering building scalable data pipelines and data products
- Strong proficiency in SQL and at least one programming language (e.g., Python, Scala, or Java)
- Proven experience building and maintaining robust data pipelines and ETL: workflows, with hands-on dbt experience for reliable, testable, and maintainable data transformations.
- Hands-on experience ingesting data from diverse sources, including APIs,: databases, SaaS applications, and event streams.
- Strong foundation in data modeling, schema design, and data quality best: practices, with functional experience working on cloud platforms like Snowflake, Redshift, BigQuery, or Databricks.
- Experience implementing CI/CD pipelines, automated testing, and data: observability to ensure reliability and trust in data systems
- Familiarity with monitoring, alerting, and incident response for production-grade data pipelines
- Proven ability to optimize performance and cost across data workflows and storage systems
