Forward Deployed Data Engineer Integration
External job listingat Hilbert
Architect data integrations for Hilbert's AI Growth Engine, working with ClickHouse, Dagster, Airbyte, Snowflake, BigQuery, and custom datasets.
Salary
Not provided
Location
San Francisco, United States
Employment type
Full time
Workplace
Not provided
Forward Deployed Data Engineer Integration
San Francisco, United States
Job description
About the role
Hilbert is a data science-first growth engine that gives B2C teams predictive clarity into user behavior, revenue drivers, and actions that drive sustainable growth. Its AI Growth Engine helps enterprises and B2C brands navigate revenue drivers in real time.
Hilbert is expanding its deployment model across managed ClickHouse data ingestion and warehouse-native logic in customer data warehouses such as Snowflake and BigQuery. The goal is to give AI agents a high-fidelity view of the business.
Responsibilities
- Architect data bridges across different customer environments.
- Support data ingestion into the ClickHouse stack using Dagster and Airbyte, or native transformations in a customer's data warehouse.
- Build metadata and business logic to help agentic flows understand custom datasets and columns.
- Prompt and partner with the Data Discovery Agent to analyze customer data.
- Help ensure consistent, high-quality AI insights regardless of where customer data resides.
Requirements
- Ability to work across both the ClickHouse ingestion and warehouse-native transformation approaches.
- Ability to define metadata and business logic for custom datasets.
Key facts
- The role involves architecting data bridges across customer environments.
- The integration approaches include ClickHouse ingestion and warehouse-native transformations.
- The stack includes Dagster and Airbyte; customer warehouses include Snowflake and BigQuery.
- The role involves defining metadata and business logic for custom datasets.
Frequently asked questions
What does this role involve?
It involves architecting data bridges across customer environments and supporting data ingestion or warehouse-native transformations. The goal is to provide AI agents with a high-fidelity view of the business.
What data integration approaches does Hilbert use?
Hilbert may ingest data into its ClickHouse stack using Dagster and Airbyte, or run transformations natively in a customer's warehouse, such as Snowflake or BigQuery.
What does the role do with custom datasets?
It defines metadata and business logic so agentic flows can understand custom columns. The role also prompts and partners with a Data Discovery Agent to analyze customer data.