Top Remote Data Engineer Jobs in Portland, OR

Build large, scalable platforms using cutting-edge data technologies. Define company data assets, own data architecture for projects, improve data quality monitoring, collaborate with cross-functional teams, design sophisticated data models.

Responsible for defining and driving data governance within the Finance organization. Partnering with leaders and process owners to implement data policies and standards, ensuring data quality and consistency across financial applications.

Seeking a collaborative Senior Data Engineer with strong experience in data modeling, SQL, Python, DBT, and Snowflake. Responsibilities include mentoring junior data engineers, building data transformations, and optimizing ETL jobs for processing large amounts of data. Must have 6+ years of experience in data engineering, a Bachelor’s degree in computer science, and proficiency in cloud native infrastructure (Azure), Docker, and object-oriented programming.

Manager overseeing Operations and Reference Data Management within the Global Clinical Data Standards. Responsible for day-to-day oversight, career development, performance objectives, and recruitment. Develops functional capabilities, maintains operational metrics, and contributes to strategic direction implementation. Ensures project delivery alignment with guidelines, drives quality standards, and engages with stakeholders for continuous improvement. Requires PMP certification, project management experience, knowledge of clinical development, drug discovery process, and project management methodologies.

As a Staff Machine Learning Engineer at Personio, you will be at the forefront of shaping their Machine Learning landscape. You will provide technical leadership, guide engineers, collaborate with cross-functional teams, and write high-quality, maintainable code. You should have a strong background in Machine Learning frameworks, including Pytorch, Tensorflow, and NLP. Additionally, you should have experience building machine learning models and a proven track record of technical leadership.

Design and lead implementation of new data systems, build scalable data pipelines, create frameworks and services for ActBlue's user-facing products, collaborate with engineering teams and data scientists, implement production-level Machine Learning platform, and optimize data infrastructure and tooling.

Build and integrate ML solutions for evaluating customer cash flow risk, support multiple products, optimize automated decisioning pipeline, experiment with modeling techniques, and partner cross-functionally with finance, product, and engineering teams.