Forward Deployed Data Engineer - LATAM

Hilbert's AI; United States; Remote; USD 150,000 - 210,000; Full time

Job summary

Hilbert is building an AI Growth Engine and looking for a Founding Forward Deployed Data Engineer in LATAM to work with customer data, architect deployments, and drive scalable integration.

You'll own LATAM deployments, decide between Managed ClickHouse or Warehouse-Native paths, and collaborate with US and Europe teams across time zones.

This remote role offers travel to customers, opportunity to shape the LATAM hub, and to build a first-class data platform for the region.

Qualifications

• Foundational data engineer skilled in ClickHouse, Snowpark, and BigQuery SQL.
• Proficient in Python for data orchestration.
• Comfortable with enterprise data architectures and semantic modeling.
• Able to work in English and Spanish with customers.
• Experience implementing data integration pipelines in cloud warehouses.

Responsibilities

• Own LATAM customer deployments from data discovery to production.
• Lead hybrid integration with ClickHouse and warehouse-native paths.
• Leverage the Discovery Agent to generate pipelines quickly.
• Construct AI semantic layer definitions for custom data.
• Model canonical representations to power ML systems.
• Serve as lead technical resource for enterprise deployments.
• Help build the LATAM playbook for processes and practices.

Skills

ClickHouse

Snowpark

BigQuery SQL

Python

Tools

Dagster

Airbyte

Discovery Agent

dbt

Job description

About Hilbert

Hilbert is a scalable, data science-first growth engine that gives B2C teams predictive clarity into user behavior, revenue drivers, and the actions that drive sustainable growth. Fully agentic by design, Hilbert shrinks months-long decision cycles to minutes.

From Fortune 10 enterprises to beloved brands like FreshDirect, Blank Street, and Levain Bakery, operators run their growth on Hilbert.

As we expand across Latin America, we're building our first technical team in the region. We're looking for founding engineers who want to work directly with customers, solve complex data problems, and help shape how Hilbert builds and operates in LATAM.

The Mission: Architect the Ground Truth

At Hilbert, we shorten \"months\" to \"minutes.\" We build the AI Growth Engine that Fortune 500 enterprises and iconic B2C brands use to navigate their revenue drivers in real time.

We are expanding our deployment model. Whether we're ingesting data into our high-performance ClickHouse managed warehouse or implementing Warehouse-Native logic directly within a customer's own data warehouse, such as Snowflake or BigQuery, the goal is the same: give our AI agents a perfect, high-fidelity view of the business.

As a Founding Forward Deployed Data Engineer in LATAM, you'll be at the center of bringing Hilbert to new enterprise customers across the region. You'll work directly with their data and technical teams, architect deployments, solve messy integration problems, and turn what you learn in the field into better infrastructure and product.

The Hard Problem: Architectural Hybridity & Semantic Clarity

The challenge isn't just moving rows; it's ensuring reasoning consistency. You're responsible for making sure our AI produces the same high-quality insights regardless of where the data resides.

Our Current Hurdles

• The Dual-Track Challenge: We're building a system that can either pipe data into our ClickHouse stack using Dagster and Airbyte, or execute \"Zero-Extract\" transformations natively in the customer's warehouse. You'll need to master both worlds.

• The AI Semantic Layer: For customers with custom datasets that don't fit our canonical models, you'll build the \"Translator\" — defining metadata and business logic so our agentic flows can understand custom data without hallucination.

• Agent-Assisted Integration: We're building a Data Discovery Agent to automate the messy parts of integration. You'll prompt and partner with this agent to analyze customer data, suggest mapping alternatives, and generate the first version of pipelines automatically, dramatically reducing integration time.

• Building in a New Market: As one of our first technical hires in LATAM, you'll help establish how we deploy, support, and scale Hilbert across the region. There won't always be an existing playbook — you'll help create it.

Who You Are

• The Pragmatic Polyglot: You're equally comfortable optimizing a ClickHouse query, writing native Snowpark or BigQuery SQL, and implementing data orchestration scripts in Python.

• The Data Ontologist: You understand that AI needs more than a table; it needs context. You have the discipline to define the meaning behind the data.

• The Translator: You can earn the trust of a customer's Data Architect, understand the logic behind custom tables and systems, and translate that complexity into Hilbert's reasoning engine.

• The Builder: You're comfortable operating in an early-stage environment where you'll encounter problems that don't yet have established processes or solutions.

• The Pilot: You're excited to use and improve AI agents that handle the heavy lifting of data discovery and pipeline scaffolding.

• The Customer Partner: You're comfortable working directly with enterprise customers, including spending time on-site when necessary to get deployments right.

What You'll Own

• LATAM Customer Deployments: Own the technical implementation of new enterprise customers across Latin America, from initial data discovery through production deployment.

• Hybrid Integration: Own the technical lifecycle of new customers, choosing and implementing the best deployment path — Managed ClickHouse or Warehouse-Native.

• Accelerated Onboarding: Use Hilbert's internal Discovery Agent to create reports and suggest mappings, moving from raw customer data to a working v1 pipeline in record time.

• AI Semantic Layer Construction: Architect semantic definitions for custom enterprise data, ensuring our agentic conversation engine has the ground truth it needs for every query.

• Canonical Modeling: Transform diverse source data into Hilbert's unified growth models to power our ML systems.

• Enterprise Deployment: Act as a lead technical resource for high-stakes enterprise implementations, ensuring our stack is performant within each customer's infrastructure.

• Build the LATAM Playbook: Help define the technical processes, best practices, and operating model we'll use as our customer base and engineering team grow across the region.

Language Requirements

• Professional fluency in English and Spanish is required. You'll work directly with customers and internal teams in both languages.

• Portuguese is a strong plus, particularly as we expand our presence in Brazil.

Bonus Points

• Deep experience with dbt for warehouse-native modeling.

• Experience working with multiple modern data warehouse solutions and understanding their respective optimization strategies.

• Experience with Semantic Layer frameworks such as Cube or MetricQL.

• Background in e-commerce, retail, marketplaces, or consumer technology, with an understanding of revenue metrics, order lifecycle, LTV, CAC, and attribution.

• Experience building an agentic workflow.

• Experience working directly with enterprise customers on complex technical implementations.

• Experience operating in an early-stage startup or building a new engineering function, market, or regional team.

Location

This role will start remotely as we build Hilbert's presence and establish our first LATAM hub.

You'll travel regularly to work directly with customers across the region, particularly during onboarding, implementation, and key deployment milestones.

As our team and customer presence grow and we establish a hub in a specific LATAM city, relocation within Latin America may be required in the future. We're looking for people who are excited about helping build that presence from the ground up and have flexibility around where the hub ultimately takes shape.

You'll also collaborate closely with Hilbert teams across the US and Europe, so comfort working across time zones is important.