Company Overview
EagleView is a premier provider of aerial imagery, property intelligence, and software solutions that are revolutionizing how industries operate. With over 300 patents and a vast geospatial data and imagery archive covering 94% of the U.S. population, EagleView delivers highly precise data. This empowers professionals in government, construction, insurance, and solar sectors to make faster, smarter, and more information.
Responsibilities
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Develop a comprehensive understanding of EagleView’s systems, applications, workflows, and operational processes to meet the organization’s data and analytics needs effectively.
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Collaborate closely with business stakeholders to document and assess workflows, business processes, and data requirements.
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Identify and define key performance indicators (KPIs) that align with strategic business goals.
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Translate business requirements into structured data models that support analytics and reporting needs.
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Design and manage conceptual, logical, and physical data models across a range of platforms and systems.
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Define critical data components, including entities, attributes, relationships, primary keys, and constraints.
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Document metadata, data definitions, lineage, and business rules to ensure clarity and consistency across the organization.
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Optimize data models to enhance performance, scalability, and maintainability—particularly in support of AI and machine learning initiatives.
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Contribute to data integrity and quality efforts by building models that support accurate, reliable reporting.
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Support database architecture, data warehouse development, and data integration projects
Requirements
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Bachelor’s degree in Computer Science, Information Systems, Data Management, or a closely related field.
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2–4+ years of hands-on experience in data modeling, database design, or data management.
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Strong knowledge of relational, dimensional, and NoSQL modeling methodologies.
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Proficient in working with SQL-based databases such as SQL Server, Oracle, or Snowflake.
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Foundational understanding of artificial intelligence and machine learning concepts.
Preferred Qualifications
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Experience conducting data profiling, schema discovery, and source-to-target mapping without complete documentation.
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Proven success in building data models tailored for AI and machine learning pipelines.
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Familiarity with cloud-based data ecosystems such as AWS, Azure, or Google Cloud Platform (GCP).
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Working knowledge of data warehousing principles and experience designing star or snowflake schema architectures.
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Skilled in using data visualization tools, especially Power BI.
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