Data Engineer

Cutsforth•Ferndale, WA

1d•Remote

About The Position

We're looking for a skilled and curious Data Engineer to join our team and help shape the future of how we use data to drive real operational outcomes. In this role, you'll design and maintain scalable data pipelines, develop and deploy AI/ML models, and work cross-functionally to turn complex datasets, including machine health and time-series data — into actionable insights. If you thrive at the intersection of engineering rigor and data science innovation, this one's for you.

Requirements

5–7 years of experience in data engineering, data science, or a related technical role
3+ years of hands-on experience with AI/ML modeling, including building and deploying models in production environments
Strong proficiency in Python for data engineering and machine learning workflows
Experience designing and managing end-end ML pipelines (data ingestion → feature engineering → model training → deployment)
Demonstrated ability to collaborate effectively across cross-functional teams
Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, or a related field
Must reside in the United States.
Successfully pass background check for cybersecurity access requirements.

Nice To Haves

Master's degree in a relevant technical discipline
Experience working with machine health datasets and/or condition monitoring applications
Background in the power, oil, or gas industry — understanding of operational data, equipment telemetry, or industrial IoT environments is a strong plus
Familiarity with time-series data modeling, forecasting, and anomaly detection techniques
Experience with cloud-based ML platforms (Azure) and orchestration tools

Responsibilities

Regularly design, develop, and maintain data pipelines and ML workflows to support operational and analytical needs
Write clean, efficient, and well-documented Python code for data processing, model development, and automation tasks
Analyze and interpret complex datasets, including time-series and machine health data to surface meaningful insights and support decision-making
Build, validate, and monitor AI/ML models in production, proactively identifying and resolving performance issues
Communicate technical findings and recommendations clearly to both technical and non-technical stakeholders across teams
Participate in cross-functional meetings and planning sessions to align data engineering efforts with broader business goals
Stay current with advancements in AI/ML techniques, tools, and industry-specific applications, particularly within power, oil, and gas environments
Document processes, models, and systems in a way that supports knowledge sharing and team continuity
Candidate will be responsible for reviewing policies and procedures related to cybersecurity and those relevant to the functions of their role.
Candidate is expected to maintain a cybersecure work environment.