Quick Overview
Job Description
Hi All,
Good Morning,
We have an urgent position for the below mentioned requirement.
Title: Geospatial Analyst
Location: Remote
Duration: Long Term
Job Summary : 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.
Experience: 10 to 14Yrs
Required Skills: Oracle, Database and SQL, Data bricks
Responsibilities:
· 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 engineer’s 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.
Qualifications:
· 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.
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