Data Engineer

Ambush is a people first company where talented, thoughtful individuals come together to build meaningful products and lasting partnerships. We believe the best work happens when people feel supported, trusted and empowered to bring their full abilities to the table.

Since 2015, because of our people first and long term mindset, we have grown into a partner relied on by some of the best companies in the world. We combine strong engineering, design and strategy with a growing strength in AI to help our clients see what is next and achieve bigger outcomes.

At the heart of everything we do is our team. We collaborate, take risks, lift each other up and take pride in doing work the right way, not settling for a quick makeshift solution. If you join Ambush, you join a group of people who want you to succeed and who show up for each other every day.

We believe in and expect real teamwork, a constant drive to be better, and delivering meaningful long term outcomes that we can be proud of together.

Role Summary

We are looking for a Data Engineer who is as comfortable optimizing a Snowflake warehouse as they are deploying an LLM-backed microservice. This is a high-impact role where you will collaborate with Product, Data Science, and Engineering to turn complex business logic into scalable, automated reality.

Key Responsibilities

Prototype and deploy scalable solutions using LangChain, LangGraph, and OpenAI SDKs to provide measurable business value.

Design and implement backend logic (Python/FastAPI) that integrates LLMs with external data sources and contextual automation.

Define and maintain secure, robust APIs that serve as the bridge between our data ecosystem and enterprise applications.

Build and optimize modular data transformations using dbt and orchestrate them via Dagster or Airflow.

Design high-performance schemas (balancing Kimball vs. OBT) that cater to both rapid experimentation and long-term reporting.

Manage and scale AI services on Cloud Platforms (GCP/AWS/Azure), ensuring low latency and stringent security.

Proven experience with Data or Analytics Engineering, ideally within a modern data stack (Snowflake, dbt, etc.).

Strong working knowledge of Python, specifically for data orchestration and building microservices (FastAPI/Flask).

You write performant, modular SQL and understand how to model data for scale.

You don't just build what's asked; you think about ROI, knowing when to automate and when to prioritize short-term delivery without sacrificing long-term quality.

Nice to Haves:

Experience building feature stores or monitoring model drift and I/O.

Familiarity with CI/CD for data, infrastructure as code, or FinOps.

Experience thriving in fast-paced environments where you might need to wear multiple hats.