Senior Data Engineer — AI-Driven Pipelines & Impact

Monograph; United States; Hybrid; USD 170,000 - 210,000; Full time

Job summary

Gusto is hiring a Senior Data Engineer to own end-to-end data solutions, shaping problems, aligning stakeholders, and delivering durable data products in collaboration with analytics, product, and engineering teams.

The role emphasizes building scalable data pipelines, applying data quality practices, and leveraging AI-driven automation to create self-service tooling for the business.

Qualifications

• 8-10+ years of industry experience in data engineering building scalable data pipelines and data products.
• Strong proficiency in SQL and at least one programming language (Python, Scala, or Java).
• Hands-on dbt experience for reliable, testable, maintainable data transformations.
• Experience ingesting data from APIs, databases, SaaS apps, and event streams.
• Foundation in data modeling, schema design, and data quality; cloud platforms like Snowflake, Redshift, BigQuery, Databricks.
• Experience implementing CI/CD pipelines, automated testing, and data observability.
• Familiarity with monitoring, alerting, and incident response for production data pipelines.
• Ability to optimize performance and cost across data workflows and storage.
• Understanding of AI/automation in data engineering and building self-service tools.
• Exemplar problem-solving and strong cross-functional teamwork.
• Strong communication and collaboration with clarity, empathy, and ownership.

Skills

Data engineering

SQL

Python/Java/Scala

APIs

Data ingestion

Data modeling

Schema design

Data quality

CI/CD

Automated testing

Data observability

Monitoring

AI automation

Problem-solving

Communication

Collaboration

Cloud platforms

Tools

dbt

Snowflake

Redshift

BigQuery

Databricks

Job description

Gusto is hiring a Senior Data Engineer to own end-to-end data solutions, shaping problems, aligning stakeholders, and delivering durable data products in collaboration with analytics, product, and engineering teams.

The role emphasizes building scalable data pipelines, applying data quality practices, and leveraging AI-driven automation to create self-service tooling for the business.