Our client, a IT Services and Consulting company, is looking for a Senior Geospatial Data Analyst - Databricks, Oracle & SQL for their Blaine, MN/ Pheasant, NE/ Hybrid location.
Responsibilities:
- GeoSpatial Analyst MAP will design and optimize advanced geospatial data solutions using Databricks, Oracle database, and SQL within a hybrid work environment.
- The role involves developing robust spatial analytics pipelines, ensuring data accuracy across complex datasets, and delivering actionable insights that guide business decisions.
- The analyst will collaborate with cross functional teams to transform location based data into strategic value for the organization and broader communities.
- Design and maintain scalable geospatial data pipelines in Databricks that integrate diverse spatial and non spatial datasets to support analytics initiatives and operational reporting.
- Develop optimized SQL queries and spatial procedures in Oracle database environments to ensure accurate retrieval, transformation, and aggregation of complex geospatial information.
- Analyze large volumes of map centric data to uncover spatial trends patterns and correlations that directly inform strategic planning and resource allocation for the organization.
- Create clear and precise geospatial visualizations and map based dashboards that help stakeholders quickly understand location based insights and make informed decisions.
- Collaborate with data engineers data scientists and business analysts to define data models for geospatial assets ensuring compatibility with existing enterprise database standards.
- Implement rigorous data quality checks and validation rules for geospatial layers and reference datasets to maintain high confidence in analytical outputs used by internal and external partners.
- Document geospatial data dictionaries processing logic and analytical methodologies so that teams can reliably reuse workflows and maintain continuity in long term projects.
- Provide expert guidance on geospatial data governance including coordinate reference systems metadata conventions and data retention practices to align with company policies.
- Evaluate new tools libraries and techniques for geospatial analysis in Databricks and related ecosystems to continuously improve performance scalability and feature depth of solutions.
- Coordinate with infrastructure and platform teams to tune Databricks clusters and Oracle database configurations so geospatial workloads run efficiently under varying data volumes.
- Support business teams by translating complex geospatial findings into concise recommendations that highlight operational efficiencies risk reduction opportunities and customer experience improvements.
- Contribute to the company purpose by using location intelligence to enhance service accessibility optimize environmental impact and support responsible growth in the communities served.
- Mentor junior analysts on best practices in geospatial analysis SQL coding standards and database design principles helping build a strong internal capability in spatial analytics.
Requirements:
- Experience: 10to14Yrs
- Required Skills: Oracle, Database and SQL, Databricks
- Possess extensive experience working with Databricks including building notebooks managing jobs and optimizing cluster usage for heavy geospatial data processing workloads.
- Hold deep expertise in Oracle database administration and development with proven ability to design tables indexes and spatial extensions that support complex analytic queries.
- Demonstrate strong proficiency in SQL covering query optimization window functions and spatial query constructs to efficiently handle large relational datasets.
- Bring solid knowledge of general database concepts such as normalization transaction management and performance tuning to maintain reliable and high performing data systems.
- Exhibit practical understanding of geospatial concepts including projections topology and spatial joins enabling accurate integration and analysis of diverse location based sources.
- Show experience operating in a hybrid work model using collaboration tools and structured communication practices to maintain alignment with distributed cross functional teams.
- Display comfort working standard day shifts with flexibility to coordinate across regions when necessary while maintaining consistent delivery on project milestones.
- Apply analytical and problem solving skills gained from at least ten years of professional experience to design robust solutions and troubleshoot complex data challenges.
- Prefer prior exposure to enterprise scale data platforms and cloud based analytics environments which strengthens ability to integrate geospatial workloads with broader data ecosystems.
Why Should You Apply?
- Health Benefits
- Referral Program
- Excellent growth and advancement opportunities