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Remote Startup Data Engineer Jobs in Oregon (NOW HIRING)

Data Engineer

OR · On-site +1

$114K - $137K/yr

About the Role As a Data Engineer focused on AI/ML , you'll build, maintain, and optimize the data ... Remote

Sr. Data Engineer

OR · On-site +1

$100K - $150K/yr

This role is remote-friendly and reports to the Manager, Data & Analytics Engineering. As a Sr. Data Engineer, your primary responsibility is to stay one step ahead of your fellow team members by ...

Data Engineer (L5)

OR · On-site +1

$380K - $610K/yr

Data Engineering at Netflix is a role that requires building systems to process data efficiently ... remote in the US with occasional visits to Los Gatos) depending on the team your skills are most ...

Data Engineer (Remote / Contract)

OR · On-site +1

$114K - $137K/yr

We are looking for a Data Engineer to join our engineering team to help us manage our diverse and growing set of initiatives. This is a fully remote, 40-hour per week contract position with the ...

Senior Data Engineer

OR · On-site +1

$105K - $143K/yr

We're a remote-first, work-anywhere, and "yes - you should make time for that adventure/vacation ... We are looking for a Senior Data Engineer to take ownership of this massive daily ingestion engine.

Senior Software Engineer (Customer Platform)

OR · On-site +1

$122K - $161K/yr

Proven ability to thrive in a remote, startup environment: A genuine interest in a high-paced, high ... developer. Additionally, we would love it if you have * Prior experience building platform or ...

Senior Full Stack Developer (Ruby on Rails)

OR · On-site +1

$150K - $180K/yr

Experience working in a remote startup environment * Hold AWS Certified DevOps Engineer - Professional or AWS Certified Developer - Associate certification * Passion for programming * Experience ...

Senior Data Engineer II, Finance

OR · On-site +1

$105K - $143K/yr

Engineering at Instacart provides the opportunity to work on challenging scaling problems while ... Experience with SOX controlled data systems. #LI-Remote

$63.75 - $82/hr

... engineering fundamentals, systems thinking, and ownership across scalable modern data ecosystems. Engagement details * Contractor / project-based engagement * Paid in USD/hour * Remote-first

ABOUT FLOVISION FloVision is a remote-first startup focused on improving the food supply chain ... On-site data collection for model training and validation * R&D visits to one of our in-person ...

Distributed Systems Engineer (L4) - Data Platform

OR · On-site +1

$114K - $137K/yr

In addition, we are open to remote candidates. We value what you can do from anywhere in the U.S ... Data Developer Experience The Data Developer Experience (DDX) team at Netflix is dedicated to ...

Senior Staff Software Engineer, Data

OR · On-site +1

$105K - $143K/yr

This is a senior individual contributor role open to remote candidates across the United States ... Partnering with Engineering to improve upstream data quality and contracts. * Leading cross ...

... and data engineers to deliver models and experimentation frameworks that inform multi-million ... If you thrive in a fast-paced environment that still moves like a startup-and you love rolling up ...

Sr. Data Analyst - Finance

OR · On-site +1

$120K - $130K/yr

You will collaborate with Data Engineering on data pipelines, identifying and solving complex data ... Fully remote within the U.S. * Open to US-based remote candidates, with a preference for PST/MST ...

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Remote Startup Data Engineer information

What is the difference between Remote Startup Data Engineer vs Remote Startup Data Analyst?

AspectRemote Startup Data EngineerRemote Startup Data Analyst
Required CredentialsBachelor's in CS, Data Engineering certificationsBachelor's in Statistics, Data Analysis certifications
Work EnvironmentBuilding data pipelines, infrastructureInterpreting data, creating reports
Employer & Industry UsageTech startups, SaaS companiesMarketing agencies, e-commerce startups
Common Search & ComparisonOften compared for technical depth and infrastructure focusCompared for data interpretation and business insights

The main difference between a Remote Startup Data Engineer and a Remote Startup Data Analyst lies in their focus areas. Data Engineers build and maintain data infrastructure, while Data Analysts interpret data to inform business decisions. Both roles are essential in startups but require different skill sets and responsibilities.

What are popular job titles related to Remote Startup Data Engineer jobs in Oregon?

For Remote Startup Data Engineer jobs in Oregon, the most frequently searched job titles are:

What job categories do people searching Remote Startup Data Engineer jobs in Oregon look for?

The top searched job categories for Remote Startup Data Engineer jobs in Oregon are:

What cities in Oregon are hiring for Remote Startup Data Engineer jobs?

Cities in Oregon with the most Remote Startup Data Engineer job openings:

Data Engineer

OR • On-site, Remote

$114K - $137K/yr

Full-time

Posted 29 days ago


Job description

About the Role

As a Data Engineer focused on AI/ML, you'll build, maintain, and optimize the data infrastructure that powers Tebra's intelligent features. You'll partner closely with Machine Learning Engineers, Data Scientists, and Software Engineers to transform complex healthcare data into high-quality datasets and real-time features that enable machine learning models.

This is a hands-on engineering role where you'll contribute to scalable data pipelines, improve data quality, and help ensure our AI systems are powered by reliable, performant, and well-governed data. You'll work on modern data platforms and gain experience building solutions that support both model training and production inference.

Your Area of Focus
  • Design, build, and maintain scalable data pipelines for feature extraction, training data generation, and model monitoring.
  • Develop and enhance data systems that support analytics and machine learning workloads, including data lakehouse and feature store technologies.
  • Monitor production data pipelines, identify data quality issues or pipeline failures, and implement improvements to ensure reliability and freshness.
  • Participate in engineering design discussions and contribute to technical decisions around data architecture and pipeline implementation.
  • Build reusable data engineering components, including automated data quality checks, schema validation, and testing frameworks.
  • Translate business requirements into scalable data solutions that enable analytics and machine learning use cases.
  • Optimize SQL queries, Spark workloads, and data processing pipelines to improve performance and scalability.
  • Collaborate with ML Engineers and cross-functional partners to support MLOps best practices, including data versioning, lineage, and reproducibility.
  • Break down technical work into manageable tasks and deliver high-quality solutions within an agile team.
Your Professional Qualifications
  • 3+ years of professional experience in Data Engineering, Software Engineering, or a related field.
  • 2+ years of hands-on experience building and maintaining production data pipelines supporting analytics, reporting, or machine learning workloads.
  • Strong proficiency in Python and SQL with experience developing production-quality data pipelines.
  • Experience with modern data processing technologies such as Spark, Airflow, Kafka, or similar distributed data platforms.
  • Experience working with cloud-based data platforms such as Databricks, Snowflake, Delta Lake, or equivalent lakehouse technologies.
  • Understanding of data modeling, data warehousing, and data governance best practices.
  • Familiarity with machine learning data workflows, including training datasets, feature engineering, and data quality concepts.
  • Experience deploying and supporting production data pipelines with monitoring, testing, and CI/CD practices.
  • Strong problem-solving skills, attention to detail, and the ability to collaborate effectively across engineering and product teams.
  • Excellent communication skills and a desire to continuously learn new technologies and engineering practices.

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