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Data Processor Jobs in Riverside, CA (NOW HIRING)

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Data Engineer

Irvine, CA · On-site

$100K - $115K/yr

Apply AI-driven techniques for anomaly detection, schema drift identification, and intelligent data processing. * Optimize Snowflake performance, scalability, and cost efficiency. * Prepare curated ...

Translate business requirements and processes into well-architected technical solutions, aligning ... Deep understanding of data modeling techniques to support technology optimization, data ...

The role involves conducting data processing, validation, and event reconstruction of tactical datasets, ensuring data integrity and supporting analytical objectives. Responsibilities : • Support ...

A Day in the Life The Processor II will be responsible for reviewing and submitting loan requests ... Maintain accurate records and data integrity within lending systems and document repositories.

This position requires the Document Processor to have strong computer skills and be a master multi ... Accurately conduct data entry and document information into the various systems (i.e., spreadsheets ...

You will be called upon to align the data available, how to access it securely, transform it, merge and fuse it with other data streams, in order to pre-process the right data and at the right ...

The ideal candidate will have a strong background in data visualization, data processing, and proficiency in Python. The Data Analyst will be responsible for transforming complex data into actionable ...

Data Specialist

Norco, CA · On-site

$31.99/hr

The position supports the Interoperability Analysis Branch by conducting data processing, data validation, and event reconstruction of combat system and Tactical Data Links (TDL) datasets. The ...

Data Specialist

Norco, CA · On-site

$31.99/hr

The position supports the Interoperability Analysis Branch by conducting data processing, data validation, and event reconstruction of combat system and Tactical Data Links (TDL) datasets. The ...

Data Specialist

Norco, CA · On-site

$31.99/hr

The position supports the Interoperability Analysis Branch by conducting data processing, data validation, and event reconstruction of combat system and Tactical Data Links (TDL) datasets. The ...

Data Entry Clerk

Murrieta, CA · On-site

$22.49 - $22.50/hr

Error-free data processing and low defect rate in entries. * Speed: High throughput per hour/day without compromising accuracy. * Confidentiality: Strict adherence to data security and privacy ...

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Data Processor information

See Riverside, CA salary details

$12

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How much do data processor jobs pay per hour?

As of Sep 13, 2026, the average hourly pay for data processor in Riverside, CA is $21.14, according to ZipRecruiter salary data. Most workers in this role earn between $16.78 and $23.32 per hour, depending on experience, location, and employer.

What is a data processor?

A data processor transfers, organizes, and processes personal data for a company. It is typically an entry-level job that serves as a starting point for a career as a data controller. As a data processor, your duties involve processing incoming documents, transferring analog documents into digital data, verifying the information in all documents, updating document formats, and creating detailed reports on company data use and management. Qualifications for this career include excellent computer skills and a bachelor’s degree in computer science or data management.

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

To thrive as a Data Processor, you need strong attention to detail, accuracy in data entry, and a high school diploma or equivalent. Familiarity with spreadsheet software (such as Microsoft Excel), database management systems, and sometimes data processing software is typically required. Excellent organizational skills, the ability to follow procedures, and effective time management make someone stand out in this role. These skills ensure data integrity, minimize errors, and support efficient information management within an organization.

What are some common challenges faced by data processors and how can they be addressed?

Data Processors often encounter challenges such as managing large volumes of data accurately and efficiently, dealing with inconsistent or incomplete data, and ensuring data privacy and compliance. To address these, it's important to develop strong attention to detail, become proficient with data processing software, and stay updated on relevant data protection regulations. Collaborating closely with data analysts and IT teams can also help resolve data issues and improve workflow efficiency.

What is the difference between Data Processor vs Data Entry Clerk?

AspectData ProcessorData Entry Clerk
Required CredentialsHigh school diploma; some roles may require basic certificationsHigh school diploma; no specialized certifications typically needed
Work EnvironmentOffice settings, data centers, or remote workOffice environments, often in administrative settings
Employer & Industry UsageBusinesses, government agencies, financial institutionsCorporations, healthcare, retail, administrative offices
Common Search & ComparisonOften compared for data handling and processing tasksCompared for data input and administrative support roles

While both roles involve handling data, Data Processors typically perform more complex data management and validation tasks, often requiring some technical skills. Data Entry Clerks focus on inputting data accurately and efficiently. Understanding these differences helps in choosing the right role based on skills and career goals.

How much does a data processor earn?

The average salary for a data processor typically ranges from $30,000 to $45,000 per year, depending on experience, location, and industry. Entry-level positions may start lower, while experienced data processors with specialized skills or certifications can earn higher wages. Many roles also offer benefits such as health insurance and paid time off.

What do you do as a data processor?

A data processor collects, organizes, and manages data to ensure accuracy and consistency. They often use software tools like spreadsheets or databases and may perform tasks such as data entry, validation, and updating records to support business operations.

What are popular job titles related to Data Processor jobs in Riverside, CA?

For Data Processor jobs in Riverside, CA, the most frequently searched job titles are:

What cities near Riverside, CA are hiring for Data Processor jobs?

Cities near Riverside, CA with the most Data Processor job openings:

Infographic showing various Data Processor job openings in Riverside, CA as of September 2026, with employment types broken down into 90% Full Time, and 10% Contract. Highlights an 85% In-person, 5% Hybrid, and 10% Remote job distribution, with an average salary of $43,977 per year, or $21.1 per hour.

Data Engineering, Senior Advisor

Pomona, CA • On-site

Other

Posted 7 days ago


Job description

Join the Clean Energy Revolution

Become a Data Engineering, Senior Advisor at Southern California Edison (SCE) and build a better tomorrow. In this job, you’ll be responsible for developing data integration pipelines (ETL) sourcing from various databases and systems. The senior advisor will develop programs using coding languages (i.e. Python, SQL) and/or low-code environments (i.e., Palantir Foundry) to create analyses and applications for stakeholders throughout Transmission & Distribution (T&D). The candidate is therefore expected to work on data governance, data architecture, data engineering solutions, and best practices for analyzing very large datasets. Additionally, the candidate will perform data mining activities to derive insights, work with cloud OLAP systems (e.g., Snowflake), and keep abreast of new and current data engineering techniques.

As a Data Engineering, Senior Advisor, your work will help power our planet, reduce carbon emissions and create cleaner air for everyone. Are you ready to take on the challenge to help us build the future?

Day In The Job
  • Manages and scales data pipelines from internal and external data sources to support new product launches and drive data quality across data products (Palantir Foundry, Snowflake, SAP Datasphere).
  • Facilitates data engineering activities covering data acquisition, extraction, normalization, transformation, management, and manipulation of large and complex data sets.
  • Keeps abreast of new and current data engineering, big data and data science techniques. Researches methods, techniques, and new practices; develops and promotes data engineering best practices, standards and guidelines.
  • Works closely with subject matter experts to design and develop front-end applications with data models and data pipelines supporting the applications.
  • Provides governance and oversight of data assets, data environments and relevant data procedures, with the proactive planning and enforcement of data asset naming conventions.
  • Builds and maintains data pipelines using big data processing technologies to process and analyze large datasets; uses ETL processes on the internal cluster.
  • Develops and maintains data warehouse schema and data models, ensuring data consistency and accuracy.
  • Ensures ongoing alignment of technical and business strategies based on changing business and technology drivers and risks.
  • Creates advanced visualizations and tools to provide insight, drives action, and supports work throughout the business.
  • Identifies and designs Data-as-a-Service candidates for improved data availability and consumption.
Responsibilities
  • Conceptualizes and owns the data architecture on behalf of the energy team in collaboration with data science and engineering teams.
  • Improves performance by optimizing computing time to process the streaming data and saves cost to company by optimizing cluster run time.
  • Identifies opportunities for building of value-added datasets to facilitate realization of enterprise use cases and for optimizing cloud costs.
  • Establishes transactional data orchestration, data lake, reporting platform strategy and roadmap formulation for data intensive enterprise transformation programs.
  • Delivers metadata management implementation to improve data governance maturity and data ownership. Oversees data platform to ensure that the service delivery is efficient and business SLAs around uptime, performance and capacity are met.
  • Designs Enterprise Data Lake to provide support for various uses cases including Analytics, processing, storing, and reporting of voluminous, rapidly changing data.
  • Designs and develops end-to-end data pipelines for the organization, resulting in improved data quality and reduced data processing time.
  • Supports Data Scientists with their development of predictive and other models, with respect to large scale datasets to address various business problems through leveraging advanced statistical modeling, machine learning and deep learning.
  • Contributes to data dictionary and data mapping from sources to the target in SCIM Data Model.
  • A material job duty of all positions within the Company is ensuring the protection of all its physical, financial and cybersecurity assets, and properly accessing and managing private customer data, proprietary information, confidential medical records, and other types of highly sensitive information and data with the highest standards of conduct and integrity.
Minimum Qualifications
  • Bachelor's Degree in Computer Science, Information Systems, Engineering, Statistics/ Mathematics or equivalent STEM major.
  • Ten or more years of experience in data processing large data sets, hands‑on with data transformation, aggregation, and filtering.
Preferred Qualifications
  • Demonstrated experience building and maintaining APIs and ETL pipelines using tools like Python, SQL, Apache Airflow, Azure Data Factory, or similar platforms
  • High competency with systems like Palantir Foundry, Snowflake,AWSor similar platforms
  • Additional certifications such as Palantir Foundry Data Engineer, Azure Data Engineer, Certified Data Management Professional, SnowPro Advanced, etc.
  • Understanding of cloud-based data storage and architecture
  • Proven ability to implement data validation, metadata management, and ensure consistency and accuracy across systems
  • Experience working in the electric utility industry or with infrastructure investment planning
  • Experience working collaboratively with cross-function stakeholders such as IT, Engineering, Planning and business teams to gather requirements and deliver tailored data solutions.
Additional Information
  • This position’s work mode ishybrid.
  • Visit our Candidate Resource page to get meaningful information related to benefits, perks, resources, testing information, hiring process, and more!
  • Qualified applications with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.
  • Position will require up to 25% traveling and being out in the field throughout the SCE service territory.
  • Relocation does not apply to this position.
About Southern California Edison

The people at SCE don't just keep the lights on. Our mission is so much bigger. We’re fueling the kind of innovation that’s changing an entire industry, and quite possibly the planet. Join us and create a future with cleaner energy, while providing our customers with the safety and reliability they demand. At SCE, you’ll have a chance to grow personally and professionally, making a real impact in Southern California and around the world.

Southern California Edison is a proud Equal Opportunity Employer, including disability and protected veteran status.

We are committed to ensuring that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodations at AskHR@sce.com or (626) 302-3456 and select option 2.

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