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Data Operations Engineer

GA Foods
St. Petersburg, USA
Full-time
Mid
Hybrid
Discovered 1 months ago
SQLPower BIMySQLExcelERPCRM

Full Job Posting

What You’ll Do

Own onboarding and maintenance of contract/configuration data (pricing, locations, customer setup, business rules)

Perform detailed review, validation, and correction of data and configuration issues

Investigate discrepancies and document resolutions

Write SQL queries for ad hoc reporting, recurring reports, and operational analysis

Maintain and support Power BI dashboards (data validation, refresh troubleshooting, logic checks)

Build reconciliation and exception reports to proactively identify data issues

Partner with Sales, Operations, Finance, and other business teams to translate requirements into accurate system setup and reporting logic

Document processes and validation steps to improve repeatability and reduce errors

Identify opportunities to strengthen data quality controls and reduce manual error

What We’re Looking For

Strong SQL skills (joins, aggregations, filtering, case logic, troubleshooting)

Experience supporting reporting/analysis in a business environment

High attention to detail and a track record of accuracy in data-related work

Experience with Power BI or similar BI/reporting tools

Strong problem-solving skills and ability to investigate root causes of data discrepancies

Clear communication skills when working with non-technical stakeholders

Ability to quickly learn new systems, business rules, and data structures

Preferred Experience

Contract pricing, customer onboarding, master data, or configuration-heavy operational systems

ERP, CRM, or other operational business platforms

Data quality controls, reconciliation processes, or audit/exception reporting

MySQL experience

Excel for validation, reconciliations, and ad hoc analysis

What Success Looks Like

Contract and configuration data is accurate and completed on time

Data issues are identified early through validation and exception checks

Reports are trusted because they are consistent and reliable

Discrepancies are resolved thoroughly with clear documentation

Processes become more structured and less error-prone over time

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