Forward Deployed Engineer

Arbol; Oregon; Hybrid; USD 120,000 - 165,000; Full time

Job summary

Arbol in Oregon is seeking a hands-on data engineer to turn loosely defined problems into structured PRDs and solid software. You’ll build internal tools, data apps, and AI-powered workflows that scale with the business.

You will write SQL and Python to analyze data, create dashboards for leadership, and integrate third-party models and data sources. The role blends prototyping in notebooks with shipping production systems.

Qualifications

• Experience turning PRDs into implemented features.
• Strong Python development and data-handling skills.
• Solid understanding of SQL, schemas, indexing, partitioning, and performance tradeoffs.
• Familiarity with statistical concepts for model evaluation.

Responsibilities

• Embed with internal teams to scope messy, loosely defined problems into structured PRDs.
• Build internal tools, pricing engines, data apps, and AI-powered workflows.
• Write SQL and Python behind analyses, dashboards, and monitoring used by leadership.
• Integrate third-party models, APIs, and data sources into systems.
• Prototype quickly in notebooks and scripts, then productionize reliable systems.

Skills

Python

SQL

PRD creation

Model evaluation concepts

Tools

Airflow

Dagster

Prefect

Kafka

SQS

Pub/Sub

Parquet

JSON

AWS

GCP

Azure

Docker

CI/CD

Job description

What You'll Be Doing

• Embed with internal teams and partners to scope messy, loosely defined problems and turn them into structured PRDs and working software
• Build and maintain internal tools, including pricing and decision engines, data apps, and AI-powered workflows
• Write the SQL and Python behind analyses, dashboards, and monitoring that leadership uses to make decisions
• Integrate third-party models, APIs, and data sources into our systems, and handle the mapping, transformation, and validation they need
• Prototype quickly in notebooks and scripts, then harden what works into reliable, tested production systems

What You'll Need

• Experience working with the product lifestyle, from PRD creation to implementation
• Solid engineering skills in Python
• Strong understanding of data systems: SQL, schemas, indexing, partitioning, and performance tradeoffs
• Comfort with statistical concepts relevant to model evaluation, or experience interpreting metrics and distributions

What's Great to Have

• Familiarity with pipeline tooling (Airflow/Dagster/Prefect), queues (Kafka/SQS/PubSub), and common data formats (Parquet/JSON)
• Familiarity with cloud infrastructure (AWS/GCP/Azure), containers, CI/CD, and basic DevOps hygiene