GC AI

Member of Technical Staff, Data Engineering

Remote - United States · Staff+

Sponsorship not specifiedDetected 36 days ago

PythonSQLBigQueryGCPTerraformRESTMachine LearningData EngineeringLLMsCRMValuationCommunication

About the role

Right now, our data lives in multiple systems: product usage, CRM, billing, customer data, user analytics.
We want someone who reaches for code, GCP primitives, and simple maintainable systems before defaulting to expensive enterprise platforms.

Build pipelines that consolidate product usage data, CRM data, billing, customer contract data, and user analytics into a single source of truth.
Design and build internal data tools using applied AI, including natural-language query interfaces and automated reporting, so the rest of the company can self-serve without waiting on an analyst.
Set up the warehouse so business teams can run their own queries and pull their own numbers without filing a ticket.
Build toward a data lake architecture that supports personalization and model fine-tuning for the GC AI product.
Builder instinct. Your default response to a data problem is to write code and build infrastructure, not to evaluate vendors and sign contracts.
Applied AI fluency. You're comfortable using LLMs and AI tooling to solve data problems: building agents that query warehouses, automating data quality checks, generating reports. You don't need to train models, but you should know how to put them to work.
Simplicity bias. You'd rather build a clean, maintainable pipeline with standard tools than an over-engineered stack that requires a team of five to operate.

5+ years of experience in data engineering, with hands-on experience building and maintaining data warehouses and pipelines.
Strong SQL skills and deep experience with BigQuery or comparable analytical databases.
Proficiency in Python for pipeline development, scripting, and tooling.
Experience working within GCP or a comparable cloud ecosystem.

This is a strong differentiator.
Experience as the first or early data hire at a startup, where you owned the full stack.
Familiarity with legaltech, legal operations, or SaaS product analytics.
Experience setting up self-serve analytics layers (semantic layers, BI tool configuration, data documentation).
Experience with data infrastructure that supports ML workflows (feature stores, training data pipelines, data lakes).
Experience with infrastructure as code, especially Terraform, for managing GCP data infrastructure.
We expect urgency, ownership, and good judgment even when things aren't perfectly clear.
If you need structure and consensus to do your best work, this isn't the right place for you.

product usage, CRM, billing, customer data, user analytics.
Your first job is to consolidate all of it into a single, well-modeled warehouse in BigQuery so the company can actually use it.

GC AI is an equal opportunity employer that supports workplace diversity and does not discriminate on the basis of race, color, religion, gender identity/expression, national origin, age, military service eligibility, veteran status, sexual orientation, marital status, physical or mental disability, or any other protected class. GC AI is committed to working with and providing reasonable accommodation to applicants with physical and mental disabilities. #LI-GCAI
To protect yourself against phishing and recruitment fraud, please note that GC AI only accepts job applications through our official careers page at https://gc.ai/careers and through sponsored jobs on LinkedIn. All legitimate communication from our team regarding job opportunities will come from a GC AI team member with a @gc.ai http://gc.ai or @getgc.ai http://getgc.ai email address.
GC AI will never:
Refer you to external websites to apply

This listing is sourced directly from GC AI's careers page and normalized into a canonical job model.