Senior Data Warehouse Specialist

Summary

SUMMARY

The Senior Data Warehouse Specialist serves as a technical leader responsible for designing, building, and maintaining advanced data warehouse and data lake solutions that integrate geospatial and alphanumeric data. This role plays a critical part in consolidating data from diverse sources, enabling advanced mapping, reporting, and self-service business intelligence (BI) capabilities across the organization. The specialist works closely with cross-functional teams to develop and optimize data architecture, support enterprise-level decision-making, and improve data accessibility and quality. This position requires a strong blend of technical expertise, strategic thinking, and the ability to translate complex data into meaningful insights that support mission goals and drive operational efficiency

COMPENSATION & BENEFITS

Salary Range: $100,000 - $118,000

Comprehensive federal benefits package available to full-time employees, including health insurance, paid time off, and retirement plan participation.

ESSENTIAL FUNCTIONS AND RESPONSIBILITIES

• Building data integrations such as geospatial and alphanumeric data warehouses and/or data lakes.
• Consolidating and geospatially enabling data, and publishing those data to meet user needs for mapping, reporting, and geospatial analysis or self-service business intelligence (BI) activities.
• Supporting GIS and alphanumeric data integration and presentation, including taking data from various sources (GIS datasets, enterprise systems, external sources) and integrating them.
• Performing data and application analysis, harvesting sources, consolidating, integrating, and publishing data.
• Performing data systems analysis and, in some cases, presenting project plans, tracking project status, and identifying risks.
• Developing a strategy for NPS data integration, including the development and implementation of any needed work plans.
• Leading reviews and helping identify key geospatial and alphanumeric data from source systems (data discovery).
• Coordinating with other project staff and stakeholders on data integration, data quality, and standards development.
• Developing and maintaining enterprise data architecture to support business requirements.
• Assessing different implementation, geospatial mapping, reporting, and visualization tools and making suggestions on best platforms.
• Analyzing data warehouse or business intelligence (BI) activities and identifying required essential resources.
• Designing different data movement processes and conducting quality control tests on data.
• Designing integration architecture, data service or exchange patterns, and conducting source to target mapping.
• Developing data lake, data warehouse, or geospatial data warehouse model and design.
• Modeling data structures and designing data/geospatial services by creating high-level logical and physical data models.
• Developing designs for all metadata relating to various Extract, Transform, and Load (ETL) or Extract/Load/Transform (ELT) processes.
• Developing and maintaining database scripts and tools to support data movement jobs.
• Using ETL, ELT, or other service-based technologies and tools to automate movement of data.
• Evaluating source systems and making recommendations for system enhancements.
• Scrutinizing NPS data infrastructure, identifying gaps, and developing plans to integrate current systems with the desired future data integration layer/model.
• Monitoring processes and developing plans to expedite gathering and accessing all relevant metadata.
• Preparing designs for needed data integration systems and recommending measures to improve performance.
• Developing and implementing geospatial and alphanumeric strategies for user access to data.
• Developing and prototype reports, dashboards, and maps for use by end users.
• Defining metadata standards for the data integration layer.
• Conducting troubleshooting on all data movement processes.
• Integration of geospatial data and database platforms with cloud-based services such as Dataverse and Data Lake.
• Implementation of available Artificial Intelligence (AI) and Machine Learning technologies to business intelligence mining.
• Providing briefings and reports on milestones status, next steps, and risks.
• Coordinating tasks with other NISC team members and stakeholders.
• Illustrating the ability to create advanced geospatial analytics and visualizations that drive strategic insights and support data-driven decision-making across the organization.

Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.