Data Engineer

Cutsforth•Ferndale, WA

6d•Remote

About The Position

We’re looking for a skilled and innovative 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, prepare and serve high-quality datasets, and partner with our data science team to support their AI/ML workflows. If you have strong data engineering fundamentals and enjoy research and development, Cutsforth is the organization for you.

Requirements

2-5 years of experience in data engineering, data science, or a related technical role
Experience with AI/ML workflows and the data needs of model development, including supporting model deployment in production environments
1-4 years of hands-on experience with Databricks for building and managing data pipelines
1-2 years of hands-on experience with Apache Spark for distributed data processing
1-3 years of experience with Microsoft Azure; equivalent experience with AWS or GCP may substitute
Strong proficiency in Python for data engineering pipelines
Strong proficiency in Python for data engineering pipelines
Strong proficiency in SQL for querying, transforming, and validating large datasets
Experience with Git and standard version control workflows, including branching, pull requests, and code review
Experience designing and managing end-to-end data pipelines (data ingestion to transformation to validation to serving)
Strong data system design skills, including data modeling and architecting scalable, reliable, and maintainable data systems
Demonstrated ability to collaborate effectively across cross-functional teams
Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related field
Successfully pass background check for cybersecurity site access

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
Experience with workflow orchestration tools

Responsibilities

Regularly design, develop, and maintain data pipelines that support operational, analytical, and machine learning workloads
Write clean, efficient, and well-documented Python code for data processing and automation tasks
Support the integration and monitoring of AI/ML models in production by delivering reliable, well-structured data pipelines
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 data engineering tools, techniques, and industry-specific applications, particularly within power, oil, and gas environments
Document processes, data models, and systems in a way that supports knowledge sharing and team continuity
Design and implement Bronze, Silver, and Gold layer pipelines to ingest, transform, and serve structured and semi-structured data
Prepare, transform, and serve datasets that support the data science team’s work in predictive analytics, anomaly detection, and operational optimization
Collaborate across engineering, operations, and product teams to understand data needs and translate them into scalable technical solutions
Operationalize and monitor the data workflows that feed deployed models, ensuring reliability and continuous improvement
Champion data quality, governance, and best practices across the data ecosystem
Contribute to the evaluation and adoption of emerging data engineering tools, frameworks, and methodologies
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.