OnStak is looking for a highly organized, detail-oriented, and dependable Data Processing Specialist to join our team. This role is responsible for ensuring that data is accurately collected, processed, validated, organized, and maintained across OnStak’s systems.
The Opportunity
The ideal candidate is comfortable working with large amounts of information, enjoys identifying and correcting errors, and understands the importance of data accuracy, confidentiality, and consistency.
As a Data Processing Specialist, you will play an important role in maintaining the quality and reliability of OnStak’s data. You will work with internal teams to process information efficiently, maintain accurate records, identify discrepancies, and help improve data workflows and processes.
This position is ideal for someone who is analytical, organized, technology-oriented, and capable of managing repetitive tasks while maintaining a high level of accuracy.
Key Responsibilities
- Enter, process, update, and maintain data across company systems and databases.
- Review information for accuracy, completeness, and consistency.
- Identify and correct data entry errors, inconsistencies, and duplicate records.
- Perform routine data validation and quality-control checks.
- Organize and maintain digital records and documentation.
- Import and export data between systems when required.
- Prepare data files, reports, spreadsheets, and summaries for internal teams.
- Follow established data-processing procedures and security requirements.
- Assist with data cleanup, migration, and database maintenance projects.
- Investigate discrepancies and work with appropriate teams to resolve data issues.
- Maintain confidentiality when handling sensitive or proprietary information.
- Track completed work and meet established productivity and accuracy targets.
- Help identify opportunities to improve data-processing workflows and reduce manual work.
- Support other data and administrative projects as needed.
Qualifications
- High school diploma or equivalent required; additional education or certification in data management, business, technology, or a related field is a plus.
- Previous experience in data entry, data processing, administrative support, database management, or a related role preferred.
- Strong attention to detail and commitment to accuracy.
- Comfortable working with spreadsheets, databases, and business software.
- Proficiency with Microsoft Excel or Google Sheets.
- Strong organizational and time-management skills.
- Ability to identify discrepancies and solve basic data-quality problems.
- Ability to manage multiple priorities and meet deadlines.
- Strong written and verbal communication skills.
- Ability to work independently as well as collaboratively.
- Ability to handle confidential information professionally.
Preferred Skills
- Experience working with CRM, ERP, database, or data-management systems.
- Familiarity with data-cleaning and data-validation processes.
- Experience working with large datasets.
- Basic understanding of data structures and database concepts.
- Experience with reporting and spreadsheet functions such as filters, formulas, lookups, and pivot tables.
- Interest in automation and improving repetitive data workflows.
What Success Looks Like
- Data is entered and maintained accurately and consistently.
- Errors and discrepancies are identified and resolved promptly.
- Data-processing tasks are completed efficiently and on schedule.
- Company records remain organized, current, and reliable.
- Data-handling procedures and confidentiality requirements are consistently followed.
- Internal teams can rely on accurate information when making operational and business decisions.
- Opportunities to improve data processes are identified and communicated to leadership.
Why Join OnStak?
At OnStak, your work will directly contribute to the accuracy, efficiency, and reliability of our operations. As a Data Processing Specialist, you will have the opportunity to work with modern technology and data systems while developing valuable skills in data management, business operations, and process improvement.