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Senior Data Engineer Jobs in Oregon (NOW HIRING)

Clarity Recruiting

$160K/yr

Implement data engineering best practices across data modeling, quality, lineage, metadata management, documentation, and operational monitoring. Develop automated data quality validation ...

Valtech

Senior Data Engineer SQL

OR · On-site +1

$155K/yr

Our borderless, global framework, which enables seamless collaboration The role For the Senior Data Engineer role, it's important to have a strong background in data engineering, specifically within ...

Instacart

Senior Data Scientist

OR · On-site +1

Roles are open at both the L5 (Senior Data Scientist I) and L6 (Senior Data Scientist II) levels ... Engineering) at a senior level. * MS/PhD in Statistics, Economics, Applied Mathematics, or a ...

Nike

Senior Data Scientist

Beaverton, OR · On-site

Build and maintain end-to-end analytical pipelines, covering data ingestion, feature engineering ... As a Senior Data Scientist, you will collaborate closely with various global teams and stakeholders ...

Valtech

Data Engineer

OR · On-site +1

$114K - $137K/yr

Our borderless, global framework, which enables seamless collaboration The role As a Sr. Data Engineer, you are passionate about experience innovation and eager to push the boundaries of what ...

New

Amerilife Group, LLC

Senior Data Architect

OR · On-site +1

$67.25 - $90/hr

Job Summary The Senior Data Architect is a senior technical leader responsible for defining ... This individual partners closely with engineering, analytics, governance, and business teams while ...

Montefiore

Senior Data Architect

Odell, OR · On-site

$69 - $92.25/hr

Evaluate and recommend technologies, tools, and platforms for data engineering, analytics, and AI ... senior leadership on data and AI architecture decisions. Mentor and guide data engineers ...

Instacart

Senior Data Engineer II, Finance

OR · On-site +1

$105K - $143K/yr

Finance data engineering is part of the Data Infrastructure team, working closely with accounting, billing & revenue teams to support the monthly/quarterly book close, retailer invoicing and internal ...

Pay Lynxs

Senior Data Integration Engineer

Portland, OR · On-site

$110 - $165/hr

PayLynxs is hiring a Senior Data Integration Engineer to join our team in Portland, Oregon! Description We are looking for a hands-on Senior DevOps Engineer to be part of our DevOps team, with a ...

PayLynxs

Senior Data Integration Engineer

Portland, OR · On-site

PayLynxs is hiring a Senior Data Integration Engineer to join our team in Portland, Oregon! Description We are looking for a hands-on Senior DevOps Engineerto be part of our DevOps team, with a ...

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Showing results 21-40

All JobsData Engineer JobsSenior Data Engineer JobsSenior Data Engineer Jobs in Oregon

Senior Data Engineer information

See Oregon salary details

$85.6K

$133.6K

$185K

How much do senior data engineer jobs pay per year?

As of Sep 5, 2026, the average yearly pay for senior data engineer in Oregon is $133,565.00, according to ZipRecruiter salary data. Most workers in this role earn between $112,100.00 and $152,200.00 per year, depending on experience, location, and employer.

What is a senior data engineer?

Senior Data Engineers are experienced professionals who design, build, and maintain large-scale data processing systems and infrastructure. They are responsible for developing data pipelines, managing databases, and ensuring the efficient flow and integrity of data across various platforms. Senior Data Engineers often collaborate with data scientists, analysts, and other engineers to support business intelligence and machine learning projects. They also play a key role in implementing best practices for data security, quality, and governance within an organization.

What are some common challenges senior data engineers face when integrating data from multiple sources?

Senior Data Engineers often encounter challenges such as inconsistent data formats, varying data quality, and differing update frequencies when integrating data from multiple sources. Addressing these issues requires designing robust ETL (Extract, Transform, Load) pipelines, implementing data validation checks, and collaborating closely with source system owners to ensure data integrity. Effective communication with cross-functional teams and leveraging scalable data integration tools are also essential to streamline the process and minimize errors.

What are the key skills and qualifications needed to thrive as a senior data engineer, and why are they important?

To thrive as a Senior Data Engineer, you need strong expertise in data modeling, ETL development, programming (such as Python or Scala), and a degree in computer science or a related field. Proficiency with big data technologies (like Hadoop, Spark), cloud platforms (AWS, Azure, GCP), and database systems, as well as relevant certifications, is highly valuable. Excellent problem-solving, communication, and leadership skills help you collaborate across teams and mentor junior engineers. These skills and qualities ensure robust, scalable data solutions that support organizational decision-making and growth.

What is the difference between Senior Data Engineer vs Data Scientist?

AspectSenior Data EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, Engineering, or related; experience with data pipelinesBachelor's/Master's in CS, Statistics, or related; proficiency in statistical analysis and modeling
Work EnvironmentBuild and maintain data infrastructure, optimize data workflowsAnalyze data, develop predictive models, generate insights
Employer & Industry UsageTech companies, finance, healthcare, where data engineering is essentialResearch, marketing, tech firms focusing on data analysis and modeling

While both roles work with data, Senior Data Engineers focus on developing and maintaining data infrastructure, whereas Data Scientists analyze data to generate insights and build models. They often collaborate but have distinct skill sets and responsibilities.

What do senior data engineers do?

Senior data engineers design, build, and maintain large-scale data pipelines and infrastructure to support data collection, storage, and analysis. They often work with tools like SQL, Spark, and cloud platforms, and may lead data team projects while ensuring data quality and security.

What are the most commonly searched types of Data Engineer jobs in Oregon?

The most popular types of Data Engineer jobs in Oregon are:

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

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

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

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

What cities in Oregon are hiring for Senior Data Engineer jobs?

Cities in Oregon with the most Senior Data Engineer job openings:

What are popular job titles related to Senior Data Engineer jobs in OR?

For Senior Data Engineer jobs in OR, the most frequently searched job titles are:

Senior Data Engineer jobs near you
Infographic showing various Senior Data Engineer job openings in Oregon as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 15% Part Time, and 3% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $133,565 per year, or $64.2 per hour.

Senior Data Engineer

Clarity Recruiting

Hybrid

$160K/yr

Full-time

Posted 24 days ago

Job description

Job Description Our client, a rapidly growing wealth management and financial services firm, is seeking a Data Engineer to join its expanding data and analytics team. This role will be responsible for designing, building, and optimizing scalable data platforms that power enterprise reporting, analytics, and business intelligence. The ideal candidate has a strong technical foundation in modern data engineering practices and enjoys partnering with cross-functional teams to deliver reliable, high-quality data solutions in a fast-paced environment.

Key Responsibilities Design, develop, and maintain scalable data pipelines, workflows, and data models to support enterprise analytics and reporting. Build and optimize ETL/ELT processes that ensure reliable, efficient, and timely delivery of business-critical data. Implement data engineering best practices across data modeling, quality, lineage, metadata management, documentation, and operational monitoring.

Develop automated data quality validation, reconciliation, and monitoring processes to ensure data accuracy, completeness, and integrity. Support enterprise analytics initiatives by translating business requirements into scalable data solutions. Partner with Analytics, Operations, and business stakeholders to deliver data products that drive informed decision-making.

Contribute to sprint planning, backlog prioritization, and execution across multiple concurrent data initiatives. Continuously identify opportunities to improve platform performance, scalability, and operational efficiency. Qualifications Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related field.

6+ years of experience in data engineering, analytics engineering, or enterprise data platform development. Experience building enterprise data platforms supporting reporting, analytics, and business intelligence. Background in financial services, consulting, or high-growth technology environments is preferred.

Strong understanding of modern data architecture, data modeling, and enterprise data management best practices. Excellent analytical, problem-solving, communication, and documentation skills. Ability to manage multiple priorities while collaborating effectively across technical and business teams.

Technical Skills Advanced proficiency with SQL, Python, and DBT. Experience designing and maintaining scalable ETL/ELT pipelines. Strong knowledge of data modeling, transformation frameworks, and enterprise data quality practices.

Experience implementing automated monitoring, validation, and reconciliation processes. Familiarity with cloud-based data platforms and modern analytics ecosystems. Strong attention to detail and commitment to building reliable, production-quality data solutions.

Compensation & Schedule Full-time Hybrid schedule (4 days onsite) Location: Austin, TX or Miami, FL Compensation up to $160,000, depending on experience Interview process includes two virtual interviews followed by a final onsite interview.

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