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Weekend Data Engineering Jobs in Oregon (NOW HIRING)

Trilon

$114K - $137K/yr

This role requires strong data engineering fundamentals, experience building data quality frameworks, and a systematic approach to defining and enforcing standards. You are detail-oriented ...

New

Bespoke Labs

Data Engineer

Eugene, OR

$115K - $138K/yr

Must-Have Skills 3+ years of data engineering experience -- pipelines, ETL, data modeling in production or research settings Strong Python proficiency (numpy, pandas, Parquet, HDF5 are daily tools ...

Bespoke Labs

Data Engineer

Portland, OR

$121K - $145K/yr

Must-Have Skills 3+ years of data engineering experience -- pipelines, ETL, data modeling in production or research settings Strong Python proficiency (numpy, pandas, Parquet, HDF5 are daily tools ...

Bespoke Labs

Data Engineer

Gresham, OR

$120K - $145K/yr

Must-Have Skills 3+ years of data engineering experience -- pipelines, ETL, data modeling in production or research settings Strong Python proficiency (numpy, pandas, Parquet, HDF5 are daily tools ...

Bespoke Labs

Data Engineer

Salem, OR

$115K - $138K/yr

Must-Have Skills 3+ years of data engineering experience -- pipelines, ETL, data modeling in production or research settings Strong Python proficiency (numpy, pandas, Parquet, HDF5 are daily tools ...

Concora Credit Inc.

Financial Data Engineer

Beaverton, OR · On-site

$119K - $143K/yr

Overview As our Financial Data Engineer, you'll help drive Concora Credit's Mission to enable ... Bachelor's Degree in Computer Science, Mathematics, Engineering, or similar field OR Equivalent ...

DMI

Data Engineer

$114K - $137K/yr

... Data Engineering Background Requirements: Must possess or be eligible to obtain and complete a Public Trust background investigation and/or a Public Trust clearance. Citizenship Status Required: Must ...

Concora Credit Inc.

Financial Data Engineer

Beaverton, OR

$119K - $143K/yr

Overview As our Financial Data Engineer, you'll help drive Concora Credit's Mission to enable ... Bachelor's Degree in Computer Science, Mathematics, Engineering, or similar field OR Equivalent ...

Concora Credit Inc.

Financial Data Engineer

Beaverton, OR

$119K - $143K/yr

Overview As our Financial Data Engineer, you'll help drive Concora Credit's Mission to enable ... Bachelor's Degree in Computer Science, Mathematics, Engineering, or similar field OR Equivalent ...

Concora Credit Inc.

Financial Data Engineer

Beaverton, OR

$119K - $143K/yr

As our Financial Data Engineer, you'll help drive Concora Credit's Mission to enable customers to ... Bachelor's Degree in Computer Science, Mathematics, Engineering, or similar field OR Equivalent ...

Pwc

Data Engineer - Senior Associate

Portland, OR

$77K - $202K/yr

In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and ...

Netflix

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 and modeling the data to power analytics. These solutions can range from batch data pipelines that ...

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Weekend Data Engineering information

What engineers make $500,000?

Senior data engineers with extensive experience, advanced skills in cloud platforms, and expertise in big data tools can earn $500,000 or more annually, especially in high-cost-of-living areas or within large tech companies. Achieving this level often requires specialized certifications, leadership roles, and a strong track record of managing complex data infrastructure.

Will AI replace ETL?

AI can automate parts of the ETL (Extract, Transform, Load) process, improving efficiency and reducing manual effort for data engineers. However, human oversight is still essential for designing, monitoring, and troubleshooting complex data workflows, so AI is more of a complement than a complete replacement for ETL roles.

Are data engineers still in demand?

Data engineers are currently in high demand due to the increasing reliance on data-driven decision making and the growth of big data technologies. Skills in cloud platforms, programming languages like Python and SQL, and tools such as Apache Spark and Hadoop enhance employability in this field.

What is the difference between Weekend Data Engineering vs Weekend Data Analysis?

AspectWeekend Data EngineeringWeekend Data Analysis
Required SkillsData pipeline development, SQL, Python, cloud platformsData interpretation, visualization, SQL, Excel
Work EnvironmentTechnical teams, data infrastructure projectsBusiness teams, reporting and insights
CertificationsData engineering certifications (e.g., Google Cloud, AWS)Data analysis certifications (e.g., Microsoft, Tableau)

Weekend Data Engineering focuses on building and maintaining data pipelines and infrastructure, requiring technical skills and cloud platform knowledge. In contrast, Weekend Data Analysis emphasizes interpreting data, creating reports, and providing insights, often using visualization tools. Both roles are essential in data-driven organizations but serve different functions during weekend projects or part-time work.

What jobs make $1,000,000 a year?

High-level executive roles such as CEOs, CFOs, and other C-suite positions can earn over $1 million annually, often including bonuses and stock options. Certain specialized professions like top-tier investment bankers, hedge fund managers, and successful entrepreneurs also reach this income level, typically requiring extensive experience, advanced skills, and significant responsibility.
What are the most commonly searched types of Data Engineering jobs in Oregon? The most popular types of Data Engineering jobs in Oregon are:
What cities in Oregon are hiring for Weekend Data Engineering jobs? Cities in Oregon with the most Weekend Data Engineering job openings:
Weekend Data Engineering jobs near you
Data Quality Engineer

Data Quality Engineer

Trilon

On-site

$114K - $137K/yr

Full-time

Posted yesterday

Job description

Trilon is building a supercharged, technology-enabled future for our people and partners. The Data Quality Engineer plays a critical role in that mission by ensuring the data that powers every AI and digital tool is accurate, consistent, complete, and trustworthy. 
This role owns data quality across the entire Data Platform, defining what good data looks like and ensuring that standard is enforced in practice. You are responsible for building the validation, monitoring, and observability systems that detect issues early and prevent bad data from reaching downstream tools where it erodes trust and usability. 
You maintain and evolve the enterprise data quality rubric, treating it as a living standard that governs how data is measured and evaluated across all pipelines and domains. You score data quality on a regular cadence and provide clear visibility into platform health, giving leadership an accurate view of where data is strong and where it needs improvement. 
You work closely with Data Engineers to embed quality checks into every pipeline, and with product and AI teams to understand how data quality issues surface in real tools. When issues arise, you trace them back to the source and resolve them at the pipeline level. 
This role requires strong data engineering fundamentals, experience building data quality frameworks, and a systematic approach to defining and enforcing standards. You are detail-oriented, structured in your thinking, and motivated by building a data foundation that engineers trust.
Data Quality Framework and Standards 
  • Define, maintain, and evolve the enterprise data quality rubric across all data domains 
  • Establish standards for data accuracy, completeness, consistency, timeliness, and reliability 
  • Ensure data quality expectations are clearly defined and consistently applied across the platform 
  • Govern how data quality is measured, scored, and reported 
Validation and Monitoring 
  • Design and implement automated data quality checks within data pipelines 
  • Build validation rules that detect anomalies, schema drift, missing data, and inconsistencies 
  • Ensure issues are identified at the source before propagating downstream 
  • Continuously improve validation coverage and effectiveness 
Data Observability and Pipeline Health 
  • Build and maintain observability systems for pipeline health, data freshness, and performance 
  • Monitor data flows for failures, delays, and unexpected changes 
  • Provide visibility into pipeline status and data quality metrics across the platform 
  • Implement alerting and reporting mechanisms for critical issues 
Issue Investigation and Resolution 
  • Diagnose data quality issues and trace them back to source systems or pipeline logic 
  • Partner with Data Engineers to resolve issues at the pipeline level 
  • Work with product and AI teams to understand how data issues impact tool behavior 
  • Ensure root causes are addressed and not repeated 
Cross-Functional Collaboration 
  • Work with the Lead Data Engineer to align on pipeline architecture and quality standards 
  • Partner with pod Data Engineers to embed quality checks into all pipelines 
  • Collaborate with Lead Engineers and Applied AI Engineers to understand downstream impacts 
  • Communicate data quality insights clearly to both technical teams and leadership 
Reporting and Continuous Improvement 
  • Score and report on data quality across the platform on a defined cadence 
  • Provide leadership with a clear view of data health, risks, and improvement areas 
  • Identify systemic issues and drive improvements in data processes and standards 
  • Continuously refine data quality practices as the platform evolves 
  • Experience designing scalable technical architectures for AI or machine learning solutions in enterprise environments 
  • Strong understanding of large language models, vector databases, embeddings, prompt orchestration, and model serving 
  • Hands-on experience with Azure services including Azure OpenAI, Azure Machine Learning, and Azure Functions 
  • Familiarity with LLM frameworks and orchestration tools such as LangChain, Semantic Kernel, or custom agent frameworks 
  • Knowledge of enterprise security, responsible AI principles, and compliance frameworks such as GDPR and CCPA 
  • Proven ability to create architecture documentation and communicate effectively with technical and non-technical audiences 
  • Experience integrating AI solutions into platforms such as Power Platform, SharePoint, and Microsoft Teams 
  • Bachelor's or master's degree in computer science, data science, engineering, or related field 
  • Certifications in cloud architecture or AI/ML disciplines preferred 

Trilon was formed with the vision of building the next Top 20 infrastructure consulting firm in North America by bringing together some of the nation's best infrastructure consulting firms, focused on delivering practical and sustainable infrastructure solutions. Trilon is backed by Alpine Investors, a PeopleFirst Private Equity Firm. Trilon currently comprises 5,500+ staff across the US. For more information, visit www.trilongroup.com.

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