Senior GIS Data Analyst (Utilities)

McKim & Creed, Inc. is seeking a Senior GIS Data Analyst to support its Water Asset Management team remotely in the Southeast. The role focuses on collecting, analyzing, and interpreting utility, GIS, IoT, and telemetry data; maintaining Esri geodatabases and asset registries; developing dashboards; and delivering actionable insights to clients and project teams.

Responsibilities:

• Conduct daily QA/QC of incoming meter, SCADA, and telemetry feeds to ensure consistency, accuracy, and completeness
• Identify and resolve discrepancies or anomalies to maintain data integrity and reliability
• Maintain and edit utility asset data in Esri geodatabases — including Utility Network and other water/wastewater asset data models — keeping attribution, connectivity, and asset hierarchies accurate and current
• Support asset registry workflows: as-built and plan-sheet incorporation, attribute population, condition and criticality fields, and reconciliation against client systems of record (Cityworks, Maximo, Lucity, Cartegraph, or similar)
• Run and document data validation, topology and network error resolution, and versioned editing workflows; maintain the supporting data dictionaries and QA checklists
• Provide daily updates to clients regarding event notifications, significant trend identifications, and actionable insights derived from data analysis
• Establish strong communication channels to foster collaboration and trust
• Perform daily inventory checks across all project locations, ensuring minimum field-deployable sensor inventory thresholds are maintained
• Collaborate with relevant teams to address inventory shortages proactively
• Maintain daily correspondence with maintenance staff to coordinate product allocations and schedule maintenance activities
• Ensure timely interventions to minimize downtime and improve operational efficiency
• Conduct weekly client meetings to review reports, discuss project progress, and identify opportunities to expand or enhance service offerings
• Build and sustain strong client relationships through consistent engagement and problem-solving

Requirements:

• • Python Programming: Proficiency in Python for data manipulation, analysis, and workflow automation (Pandas, NumPy, Matplotlib preferred)
• • SQL & Database Management: Strong SQL skills for querying and managing large relational datasets; experience optimizing queries and ensuring data efficiency
• • Spatial Data Engineering: Experience designing and maintaining spatial data pipelines — ingesting, transforming, and publishing geospatial and time-series data across systems; spatial SQL (PostGIS or ArcSDE), coordinate systems and projections, and schema design for large multi-source datasets
• • AI-Assisted Development: Practical use of AI coding assistants and agentic tools (Claude, Copilot, or similar) to build internal applications, analysis tools, and automation — with sound judgment about where AI-generated output requires review, testing, and validation before it reaches a client deliverable
• • MCP & AI Integration: Familiarity with Model Context Protocol (MCP) and similar integration patterns for connecting AI tools to data sources, APIs, and internal systems; interest in building and maintaining connectors that make utility data accessible to AI-assisted workflows
• • ArcGIS Pro: Comfortable with spatial analysis, mapping, and basic geoprocessing for QA/QC and reporting workflows
• • Geodatabases & Utility Asset Data Models: Working knowledge of geodatabase structure — feature classes, domains, subtypes, and relationship classes — and familiarity with utility asset data models such as the Esri Utility Network or comparable water, sewer, and stormwater schemas
• • Asset Data Editing & Validation: Comfortable editing asset features, resolving validation and connectivity errors, and working within an established editing and QA process
• • Survey123 & Field Maps: Comfortable using deployed forms, validating field-collected data, and troubleshooting field-side issues
• • Operations Dashboard & Experience Builder: Comfortable navigating and interpreting client-facing dashboards and apps
• • Bachelor's degree in Geography/GIS, Data Science, Computer Science, Engineering, or related field
• • 7–10 years of professional experience in data analysis, GIS, or IoT-related analytics
• • Hands-on exposure to the Esri Utility Network — you have worked inside a UN-based dataset (editing, validating, tracing, or analyzing), even if configuration and administration were handled by others
• • Strong analytical and problem-solving skills with the ability to interpret complex data and deliver meaningful insights
• • Excellent written and verbal communication skills; comfortable engaging with clients and cross-functional teams
• • Highly organized, self-motivated, and able to manage multiple tasks in a remote environment
• • Valid driver's license and acceptable motor vehicle and criminal record
• • Direct utilities data experience — water, wastewater, or related utility sector
• • Deeper Utility Network work beyond day-to-day editing — asset package configuration, network rules, subnetwork and trace workflows, or migration from a geometric network
• • Experience integrating GIS with enterprise asset management or CMMS platforms (Cityworks, Maximo, Lucity, Cartegraph)
• • Familiarity with asset management program fundamentals — condition assessment, criticality and risk scoring, renewal planning, and levels of service
• • ArcGIS Enterprise/Portal experience, including branch versioning, service publishing, and data migration from CAD or legacy systems
• • Background in non-revenue water (NRW) programs, leak detection workflows, or wastewater inflow/infiltration (I&I) work
• • Experience with data QA/QC workflows from field collection through delivery
• • Experience building API integrations to telemetry vendors (Ovarro, Trimble, Sentryx, Ayyeka, DataGate, etc.) or SCADA systems
• • Early exposure to Survey123 form authoring, Experience Builder, or ArcGIS API (Python or JavaScript) work
• • Familiarity with Grafana, Power BI, or similar dashboarding platforms for time-series and event visualization
• • Demonstrated examples of tools, scripts, or applications you built with AI assistance — and the ability to explain what you validated and how
• • Experience with cloud data platforms (Azure, AWS) and orchestrated pipelines for utility or sensor data at scale
• • Demonstrated ability to translate data into clear, actionable insights for clients