GIS Specialist – Utility Mapping, Data Quality & Data Acceptance Testing
Walnut Creek, Contra Costa County, California, 94598, USA
Listed on 2026-06-12
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Engineering
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IT/Tech
Data Analyst, Data Scientist
Overview
GIS Specialist – Utility Mapping, Data Quality & Data Acceptance Testing (DAT)
Location: San Francisco Bay Area or Remote work from home eligible (U.S. based)
Employment Type: Full-Time
About Celerity
Celerity is an agile risk optimization company that empowers public utility organizations by converting complex data into clear, actionable intelligence to mitigate risk, optimize assets, and maximize project results. We partner with utilities across the United States to solve complex operational, data, and compliance challenges through a combination of deep industry expertise, advanced analytics, and practical execution. Our teams operate at the intersection of engineering, GIS, data, and program management to drive measurable, field-impacting results.
Position Overview
This GIS Specialist position supports mapping, data validation, and quality assurance activities for electric utility asset systems. This role plays a key part in executing Data Acceptance Testing (DAT) workflows, including validation of conflated datasets derived from multiple systems of record (e.g., GIS, SAP, engineering records, and field data). The GIS Specialist will ensure that integrated asset data meets defined acceptance criteria, quality standards, and program requirements.
The ideal candidate is detail-oriented, process-driven, and experienced working with conflated or integrated utility datasets, with a strong emphasis on data accuracy, traceability, and quality.
- GIS Mapping & Data Maintenance
- Perform GIS editing and data remediation for electric utility assets
- Update and maintain spatial and attribute data in accordance with defined standards and workflows
- Support data cleanup initiatives to improve overall asset data quality and confidence
- Ensure alignment between GIS, engineering records, and system-of-record data sources
- Data Acceptance Testing (DAT) Execution
- Execute Data Acceptance Testing (DAT) workflows across conflated GIS and asset datasets
- Perform detailed review and validation of conflated data outputs, ensuring alignment between source systems (e.g., GIS, SAP, engineering records, and field-collected data)
- Validate spatial and attribute accuracy of assets resulting from conflation processes (merging, alignment, and reconciliation of disparate datasets)
- Apply standardized QA/QC protocols and acceptance criteria to determine data acceptance or rejection
- Conduct structured sampling (e.g., statistically valid sampling approaches) to validate overall data quality
- Identify, document, and categorize defects, discrepancies, and misalignments introduced through conflation or data integration processes
- Support root cause analysis of data issues related to source system inconsistencies, transformation logic, or conflation workflows
- Performance Tracking & Reporting
- Track and log effort, cycle time, and complexity associated with each DAT task
- Maintain detailed records of throughput (e.g., records/assets reviewed per day/week)
- Contribute to development of unit-based performance benchmarks and productivity models
- Provide input into reporting on data quality trends, defect rates, and process efficiency
- Data Validation & Ingestion Support
- Validate field-collected, legacy, and third-party data prior to system integration
- Support ingestion workflows into GIS and related systems of record
- Identify data gaps and coordinate resolution with cross-functional teams
- Ensure data consistency across multiple platforms (e.g., GIS, SAP, document repositories)
- Quality Assurance & Continuous Improvement
- Participate in QA/QC reviews to ensure compliance with program standards
- Provide feedback on workflow inefficiencies, tooling limitations, and automation opportunities
- Support continuous improvement of DAT processes and data validation methodologies
- Contribute to documentation of workflows, standards, and best practices
- Collaboration & Coordination
- Work closely with program managers, quality teams, and engineering resources
- Coordinate with field validation teams and data providers to resolve discrepancies
- Support alignment across GIS, data, and program work streams
- Participate in structured program cadences (e.g., weekly status meetings,…
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