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Hilbert

No-code AI analytics for B2C growth

Delivery Engineer - Data, Americas

Data EngineeringUpdated on Nov 13
Full-timeNo salary listed

About the Job

Requirements

  • Extensive data engineering experience, including expert SQL and data modeling, strong Python, and dbt or Spark.
  • Hands-on experience with Databricks, Snowflake (including Snowpark) or BigQuery, and ClickHouse, plus an orchestrator such as Dagster or Airflow.
  • Working knowledge of cloud identity and access management and networking on AWS, Azure or GCP.
  • Comfort working in a distributed team across time zones.
  • Fluency in Spanish for roles based in Latin America.

Responsibilities

  • Work with customer engineers to understand their data sources and help build the Data Discovery Agent, which analyzes data, suggests mappings, and scaffolds initial pipelines.
  • Map source data into Hilbert's unified growth models and help shape new models for industries not yet served.
  • Build and run ETL and ELT pipelines through Hilbert's data orchestration layer, using either Hilbert's stack or the customer's warehouse.
  • Define metadata, metrics, and business logic in the Cube-based semantic layer so AI agents can interpret custom data accurately.
  • Connect Hilbert and customer cloud environments using least-privilege access and private connectivity.
  • Own monitoring and data quality checks until deployment is production-ready, and maintain data quality thereafter.
  • Turn repeated delivery work into product in collaboration with the product engineering team.

Desired Qualifications

  • ML engineering experience.
  • DevOps, software architecture, and security knowledge.
  • Experience with growth-focused data projects.
  • Industry experience in e-commerce, retail, fintech, telecommunications, or media.
  • Ability to travel to the US when necessary.

About the Company

Hilbert

No-code AI analytics for B2C growth

Hilbert provides an AI-powered growth platform for B2C businesses that turns fragmented data from teams like retail, inventory, and ecommerce into actionable guidance. It connects diverse data sources, uses deep learning and a proprietary AI/ML stack to organize data for models, and offers a no-code, natural language interface to ask questions. The Hilbert Label collects all data about a single customer, including predictive insights such as churn risk and upsell potential, and updates this label as new data arrives; the system also flags marketing inefficiencies and forecasts metrics like customer growth. Its goal is to translate insights into measurable actions with estimated revenue impact, helping large B2C brands shorten decision cycles and accelerate growth while expanding through venture funding and experienced operators.

Company size
51-200
Company stage
Series A
Total funding
$28M
Headquarters
San Francisco, CA
Founded
2025

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