> Markdown version of [/jobs/ext/2979676-geospatial-sr-analyst-map-gssanl](https://www.wearedevelopers.com/jobs/ext/2979676-geospatial-sr-analyst-map-gssanl). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# GeoSpatial Sr.Analyst MAP - GSSANL

- **Company:** Ipolarity LLC
- **Location:** Norfolk, VA, United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Geographic Information Systems, Artificial Intelligence, Data Analysis, Big Data, Code Review, Data Structures, Geocoding, Software Product Management, Reference Data, Spatial Data Infrastructures, SQL Databases, Data Layers, Data Lineage, Databricks
- **Published:** September 18, 2026
- **Apply:** https://www.careerjet.com/jobad/usc1ac3233d26c103b7c2990222c3aac60

## About the Role

model assessment sessions to ensure that semantic structures remain scalable, maintainable, and aligned with enterprise standards. -Engage with user groups and support channels to troubleshoot issues in map based analytics, identify semantic model enhancements, and prioritize backlog items that deliver the greatest value. -Coordinate with platform teams to evaluate new Databricks features and geospatial libraries and to integrate them into existing patterns where they add measurable benefit. -Contribute to continuous improvement initiatives that reduce manual geospatial data preparation steps and increase the speed at which new map based insights reach decision makers. -Qualifications -Combine six to eight years of experience in geospatial analytics or spatial data engineering with a strong track record of applying ontology and semantic modeling techniques in production environments. -Apply extensive hands on experience with Databricks platforms and Unity Catalog to design secure,
discoverable, and well governed data and semantic layers for geospatial use cases. -Demonstrate advanced proficiency in artificial intelligence and business intelligence use cases using AI and BI assistant tools to accelerate exploration of geospatial patterns and map based insights. -Leverage strong skills in spatial data processing, geocoding, coordinate reference systems, and spatial joins to construct robust semantic layers that support diverse downstream models. -Use solid experience in SQL, data modeling concepts, and analytics best practices to design semantic structures that are efficient, explainable, and easy for analysts to adopt. -Exhibit excellent communication, documentation, and stakeholder collaboration capabilities to translate complex geospatial and semantic concepts into language that non technical partners can act upon. -Showcase a passion for ethical and inclusive data use with an emphasis on geospatial solutions that improve accessibility,
sustainability, and equitable outcomes for communities served by the company. 9.Job Location : Primary :USVANOFC01 Norfolk - VA USA, CLT/RMT Alternate : , 10.Job Type : 60CW00 Business Associate 11.Demand Requires Travel? : N 12.Certifications Required : NA 13.Work Model : Hybrid 14.Sub Contractor allowed : Y

## Description

1.Job title : AI Product Owner 2.Job summary : Serve as a Product Owner specializing in ontology and semantic modeling for artificial intelligence to design, govern, and optimize spatial data assets on Databricks platforms in a hybrid work model. Collaborate with AI and BI teams to deliver accurate map driven insights that improve decisions across global markets and create positive outcomes for customers and communities. 3.Experience : 6to8Yrs 4.Required Skills : 5.Nice to have skills : 6.Technology : -Not Applicable 7.Shift : Day 8.Responsibilities : -Design comprehensive geospatial ontologies that accurately represent locations, networks, and spatial relationships to support advanced artificial intelligence and business intelligence use cases across multiple domains. -Develop semantic models that unify geospatial, transactional, and reference data into a consistent knowledge layer that improves accuracy and interpretability of AI driven analytics. -Implement and maintain
geospatial data pipelines on Databricks using Unity Catalog to ensure strong governance, lineage tracking, and reusable data products for mapping and spatial analysis. -Optimize data structures, partitioning strategies, and query logic on Databricks to deliver performant spatial analytics for large scale datasets across markets and business functions. -Create geospatial feature datasets and semantic layers that can be consumed by AI and BI Genie tools to enable self service insights for analysts and business partners. -Collaborate with data scientists, data engineers, and mapping specialists to translate geospatial business requirements into semantic models and ontology structures that can be operationalized in production. -Define and document standards for geospatial data quality, metadata, and semantic definitions to ensure consistent interpretation and reuse across projects and regions. -Build curated geospatial datasets that align with privacy, compliance, and ethical use requirements
while still enabling innovative artificial intelligence driven spatial solutions. -Analyze existing map based workflows and reports to identify semantic gaps, harmonize location related dimensions, and reduce duplication of geospatial logic across teams. -Partner with product and operations stakeholders to design spatial metrics and geocoding strategies that directly improve customer experience, resource allocation, and societal impact outcomes. -Develop validation and reconciliation processes that compare semantic models with ground truth data and external geospatial sources to continuously improve reliability. -Produce clear technical documentation, semantic dictionaries, and usage guidelines that help downstream users understand and correctly apply geospatial ontologies and models. -Guide peers in adopting Databricks Unity Catalog capabilities for cataloging, securing, and sharing geospatial assets in a governed and auditable manner. -Participate in code reviews, design discussions, and


## Related Videos

- [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology)
- [Best practices: Building Enterprise Applications that leverage GenAI](https://www.wearedevelopers.com/videos/1513-best-practices-building-enterprise-applications-that-leverage-genai)
- [WeAreDevelopers LIVE - CODE100 at WeAreDevelopers Europe](https://www.wearedevelopers.com/videos/2132-wearedevelopers-live-code100-at-wearedevelopers-europe)
- [Fully Orchestrating Databricks from Airflow](https://www.wearedevelopers.com/videos/336-fully-orchestrating-databricks-from-airflow)
- [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data)
- [Generate AI in the Browser with Chrome AI - Raymond Camden](https://www.wearedevelopers.com/videos/1770-generate-ai-in-the-browser-with-chrome-ai-raymond-camden)

## Related Articles

- [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering)
- [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk)
- [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers)
- [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story)
- [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers)
- [Everything a Developer Needs to Know About MCP with Neo4j](https://www.wearedevelopers.com/magazine/604-everything-a-developer-needs-to-know-about-mcp-with-neo4j)