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Weekend Data Jobs in Oregon (NOW HIRING)

Data Engineer - AI

$105K - $125K/yr

Extend your support to after - hours or weekends as needed. * Create and maintain data pipelines as needed. * Validates the tasks results to ensure that all the requirements are met. * Adhere to all ...

Data Analyst Job Details Activities could include but is not limited to the following: Analysis of data to find patterns, Development of applications for data gathering and analysis, Developing ...

Data Analyst Location : Salem Oregon duration : 6+months : * Analyze ODOT Asset Management systems and databases and document the current state this would include SQL, Oracle, Access, GIS, etc.

Data Analyst Procom is a leading provider of professional IT services and staffing to businesses and governments in Canada. With revenues over $500 million, the Branham Group has recognized Procom as ...

With the ability to easily enrich customer data and rapidly launch growth experiments, Airship enables brands to deliver consistent, meaningful interactions that accelerate conversion and foster ...

... data collection and analysis of all software and hardware throughout the enterprise and cloud to identify, analyze and recommend changes to software and hardware purchases, inventories, reporting ...

Ensuring data quality flows according to the expectation of tools. 3. Microsoft Access: Data ingestion tools & database design/management is required as well. The candidate will be responsible for ...

Data Analyst Job Details The successful candidate for this position will provide operational reporting and analysis in support of the B2B marketing strategy for digital content. Coordinating efforts ...

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Weekend Data information

See Oregon salary details

$9

$19

$46

How much do weekend data jobs pay per hour?

As of May 28, 2026, the average hourly pay for weekend data in Oregon is $19.30, according to ZipRecruiter salary data. Most workers in this role earn between $13.43 and $19.42 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Weekend Data Analyst, and why are they important?

To thrive as a Weekend Data Analyst, you need strong analytical skills, proficiency in data interpretation, and typically a degree in statistics, mathematics, or a related field. Familiarity with data analysis tools like Excel, SQL, Python, or BI platforms, and sometimes relevant certifications, is commonly required. Attention to detail, time management, and effective communication are crucial soft skills for managing weekend workloads and sharing insights with stakeholders. These competencies ensure accurate, timely analysis and actionable reporting even within limited weekend hours.

What are the main responsibilities and challenges of working as a Weekend Data Analyst?

As a Weekend Data Analyst, your primary responsibilities include collecting, cleaning, and analyzing data to provide insights for decision-making, often focusing on time-sensitive projects or monitoring systems that require weekend support. A common challenge in this role is managing tight deadlines and ensuring data accuracy with limited weekday resources or support. You may work independently or as part of an on-call rotation, collaborating remotely with teams to deliver timely reports or troubleshoot issues. This position offers valuable experience for those seeking to build expertise in fast-paced analytics environments and demonstrates reliability for future advancement.

What are Weekend Data jobs?

Weekend Data jobs refer to positions that involve working with data—such as data entry, analysis, or reporting—specifically during weekends. These roles are often part-time and may appeal to students, professionals seeking extra income, or those with weekday commitments. Weekend Data jobs can be found in industries like retail, healthcare, and IT, where data needs to be processed continuously. Common responsibilities include managing databases, cleaning data, and generating reports. Working these hours may also offer flexible scheduling or remote work opportunities.

What is the difference between Weekend Data vs Weekend Data Analyst?

AspectWeekend DataWeekend Data Analyst
Required CredentialsTypically a background in data management or related certificationsSame as Weekend Data, often requiring data analysis certifications or skills
Work EnvironmentPart-time or weekend-focused data management rolesPart-time or weekend-focused data analysis tasks, often in office or remote settings
Employer & Industry UsageUsed in industries needing weekend data processing, like retail or logisticsUsed in industries requiring weekend data insights, such as marketing or e-commerce

Weekend Data and Weekend Data Analyst roles share similar credentials and work environments, focusing on weekend or part-time data tasks. The main difference lies in the job focus: data management versus data analysis. Both roles serve industries that need weekend data support, but the analyst role emphasizes interpreting data to inform decisions.

What are the most commonly searched types of Data jobs in Oregon? The most popular types of Data jobs in Oregon are:
Data Architect Manager

Data Architect Manager

Roseburg Forest Products

Springfield, OR • On-site

Full-time

Posted yesterday


Roseburg Forest Products rating

7.7

Company rating: 7.7 out of 10

Based on 22 frontline employees who took The Breakroom Quiz


Job description

Description
Purpose
The Data Architect Manager will lead and oversee the organization's enterprise data platforms, database operations, and data architecture initiatives to ensure scalable, secure, and reliable data systems that support business and analytics needs. This position will also manage and develop cross-functional data teams while driving data governance, system improvements, and strategic data solutions that align with organizational objectives.
Key Responsibilities
  • Manage and guide projects to improve the usability, scalability, efficiency, and security of the organization's data resources. It can include data migrations, data governance initiatives, data management and architecture projects.
  • Responsible for overseeing maintenance and support of enterprise data collection systems and data analytic platforms.
  • Help align data systems with data solutions, modeling, and analytics initiatives.
  • Facilitate the resolution of escalated issues arising from operations and requiring coordination with other departments.
  • Implement and improve new or existing data collection systems and solutions.
  • Oversee day-to-day database operations including availability, performance, backup and recovery, and operational issue resolution.
  • Manage, coach, and develop team members across the data organization
  • Partner with Business Analysts and Project Managers to determine the scope and effort for projects, gather and document business and data requirements, develop solutions or work with external resources to develop solutions meeting the needs of the business
  • Guide OLTP and OLAP design methodologies to ensure transactional and analytical systems are appropriately designed, performant, and aligned with business and reporting needs.
  • Apply EDV 2.0 methodology to support consistent, scalable, and governed data warehousing practices.
  • Oversee the use of Qlik Replication and Qlik Compose (Stages 1 and 2) to support data ingestion, transformation, and delivery across enterprise data platforms.
  • Promote and model company core values while maintaining a calm, solutions-focused approach in both routine operations and high-impact situations.
  • Perform other related duties as assigned

Required Qualifications
  • Bachelor's degree in business or computer information systems and 7+ years of experience in IT Operations with a strong understanding of database structures, theories, principles, and practices; or an equivalent amount of education, training, or experience
  • High-level knowledge of databases and data warehouse technologies.
  • Experience with SQL Server and Tools (SSMS).
  • Proficiency with Qlik Replication and Qlik Compose (Stages 1 and 2) to support data ingestion, transformation, and delivery across enterprise data platforms.
  • Experience with OLTP and OLAP design principles and data modeling for both transactional and analytical environments.
  • Proficiency with EDV 2.0 methodology to support governed, scalability, and consistent data warehousing practices across the enterprise.
  • Strong analytical and problem-solving skills; ability to work independently or collaboratively
  • Effective communicator across all levels of the organization
  • Ability to keep a level head and positive attitude regardless of situation.
  • Flexibility to work after-hours or weekends and travel to various business locations as needed

Preferred Qualifications
  • Previous management experience

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