You'll work between data science, analytics, BI, and client teams. You'll be the person who turns a business question into a data design, and the one who keeps a platform running that serves every discipline on the account.
AI and ML work is moving from experimentation into production across our client environments. You'll help make that happen by building the data plumbing that lets models and agents run reliably inside GCP, instead of stalling in a notebook.
What You'll Do
Build the Pipelines That Power Client Analytics
Design, build, and maintain batch data pipelines on GCP using BigQuery, Dataform, Cloud Composer/Airflow, and Dataflow. Take a SQL-first approach and build to scale as client data grows.
Write and optimize complex SQL that keeps BigQuery fast and costs predictable.
Build external data API integrations on Cloud Run to bring third-party and platform data into a single, usable environment.
Own Data Quality End to End
Own the validation and cleansing pipelines that catch data problems before they reach a dashboard, a model, or a client.
Troubleshoot pipeline failures quickly, including tracing issues upstream, and fix root causes so the same failure doesn't come back.
Fuel Data Science and Analytics
Partner with data scientists and analysts to deliver reliable, well-documented datasets that shorten the path from question to insight.
Work with the data science team on AI/ML integrations in GCP so models can move into production workflows.
Translate Business Questions into Data Solutions
Lead requirements conversations with client and internal stakeholders, and turn loosely defined asks into clear data designs.
Build and maintain dashboards and handle ad-hoc client data requests. Where it makes sense, turn one-off requests into repeatable assets.
Engineer with Discipline
Use Git, pull request workflows, and CI/CD automated deployments to ship changes safely and often.
Raise the team's engineering standards through code reviews and shared best practices.
What You'll Need
Bachelor's degree in computer science, engineering, information systems, or a related field, or equivalent experience
3+ years of data engineering experience, including production batch pipelines on GCP (BigQuery, Cloud Composer/Airflow, Dataflow)
Advanced SQL skills, with experience building SQL-first pipelines in BigQuery
Strong Python skills
Experience building API integrations, ideally on Cloud Run
Hands-on experience with version control and CI/CD (Git, PR workflows, automated deployments)
Ability to gather requirements from technical and non-technical stakeholders, and confidence working directly with clients
The judgment to make design tradeoffs and explain them clearly
Future-Ready Skills (Nice to Have)
Experience with Dataform or dbt for modular, tested, version-controlled transformations
Experience building with Gemini Enterprise agents (formerly Vertex AI)
Background in consumer or marketing data, such as CRM, campaign response, or customer identity data
Experience using AI-assisted development tools to speed up pipeline builds, testing, and documentation
Benefits
We believe great work happens when people have the support and flexibility they need to thrive. Our benefits include medical, dental, and vision coverage, a 401(k) retirement plan, paid holidays, and Flexible Time Off (FTO) so you can take time away to recharge when you need it. We also offer additional programs focused on wellness, financial security, and professional growth.
We are an equal opportunity employer
We believe that innovative ideas and solutions start with unique perspectives. That's why we're committed to providing every employee a workplace that's free of discrimination and intolerance. We're proud to be an equal opportunity employer and actively search for like-minded people to join our team.
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform job functions, and to receive benefits and privileges of employment. Please contact us to request accommodation.
