Forward Deployed Data Engineer – Integration

Hilbert's AI

Forward Deployed Data Engineer architecting high-performance data bridges for AI growth engine. Collaborating with enterprise clients to implement tailored data solutions in hybrid environments.

Posted 7/14/2026full-timeSan Francisco • California • 🇺🇸 United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in managing the technical lifecycle of customer implementations, utilizing dbt for warehouse-native modeling, and optimizing data warehouse solutions. Proficient in architecting semantic definitions and transforming diverse data sources into unified growth models for machine learning applications.

Highest-signal resume keywords

Deep Experience With DbtData Warehouse Solutions OptimizationSemantic Layer FrameworksE-Commerce/Retail BackgroundAgentic Workflow Development

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

DbtData Warehouse ModelingSemantic Layer FrameworksData TransformationMachine Learning Systems

Tools & Technologies

Hilbert Discovery AgentClickhouse

Industry Keywords

E-CommerceRetailRevenue MetricsOrder LifecycleLTVCACAttribution

About the role

Key responsibilities & impact

Own the technical lifecycle of new customers, choosing and implementing the best deployment path (Managed Clickhouse vs. Warehouse-Native)
Use Hilbert internal Discovery Agent to create reports and suggest mappings, moving from raw data to a working v1 pipeline in record time
Architect the semantic definitions for custom enterprise data, ensuring our agentic conversation engine has the Ground Truth for every query
Transform diverse source data into Hilbert unified growth models to power our generic ML systems
Act as the lead technical resource for high-stakes enterprise implementations, ensuring our stack is packaged and performant in their specific infra

Requirements

What you’ll need

Deep experience with dbt for warehouse-native modeling
Experience with more than one state of the art data warehouse solutions and knowing the optimization strategies
Experience with Semantic Layer frameworks (Cube, MetricQL, etc.)
Background in E-commerce/Retail (understanding Revenue Metrics, Order lifecycle, LTV, CAC, and Attribution etc.)
Having built an agentic workflow before

Benefits

Comp & perks

Competitive salary + equity package
Performance-based bonuses tied to project milestones and customer impact