Data Warehousing Specialist

CIYIS LLC; Denver (CO); On-site; USD 90,000 - 130,000; Full time

Job summary

A leading company is seeking a Senior Data Warehouse Specialist with expertise in geospatial and alphanumeric data integration. Responsibilities include developing data strategies, managing data quality, and implementing various data integration tools. The ideal candidate will have a Bachelor’s or Master’s degree and 3-7 years of relevant experience, alongside strong technical skills in SQL, Python, and ETL frameworks.

Qualifications

• 3–7 years of experience in data engineering or business intelligence roles.
• Strong understanding of data warehousing and data lake architectures.
• Preferred certifications: Google Cloud Professional Data Engineer, AWS Certified Data Analytics.

Responsibilities

• Develop a strategy for client data integration.
• Define data integration requirements and leverage pilot projects.
• Analyze BI activities and identify required resources.

Skills

SQL

Python

ETL frameworks

Data modeling

Data governance

Problem-solving

Education

Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems

Tools

Apache Airflow

dbt

Talend

PostgreSQL

SQL Server

MongoDB

ArcGIS

QGIS

AWS

Azure

GCP

Job description

Senior and Journey Data Warehouse Specialist

We are seeking Data Warehousing Specialist(s) in Geospatial and Alphanumeric Data Integration, Geospatial Mapping, and Business Intelligence Services. This role involves 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 activities.

Key Responsibilities

• Develop a strategy for client data integration including the development and implementation of work plans.

• Define data integration and lifecycle requirements; leverage pilot projects to demonstrate functionality.

• Identify key geospatial and alphanumeric data from source systems and perform data discovery.

• Coordinate with stakeholders on data integration, data quality, and standards development.

• Develop and maintain enterprise data architecture to support business requirements.

• Assess and recommend geospatial mapping, reporting, and visualization tools.

• Analyze BI activities and identify required resources.

• Design data movement processes and conduct quality control tests.

• Develop data lake, data warehouse, or geospatial data warehouse models.

• Create logical and physical data models for alphanumeric and geospatial data.

• Develop metadata designs for ETL/ELT processes.

• Maintain database scripts and tools to support data movement jobs.

• Automate data movement using ETL/ELT or service-based technologies.

• Evaluate and recommend enhancements to source systems.

• Identify gaps in data infrastructure and develop integration plans.

• Monitor metadata gathering processes and develop access strategies.

• Prototype reports, dashboards, and maps for end users.

• Define metadata standards for the integration layer.

• Troubleshoot and resolve data movement issues.

• Integrate geospatial data with cloud-based services like Dataverse and Data Lake.

• Implement AI and Machine Learning technologies for BI mining.

• Provide briefings and reports on milestones, risks, and next steps.

• Coordinate tasks with client team members and stakeholders.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or a related field.

• 3–7 years of experience in data engineering, data integration, or business intelligence roles.

• Proficiency in SQL, Python, and ETL frameworks (e.g., Apache Airflow, dbt, Talend).

• Experience with relational databases (e.g., PostgreSQL, SQL Server) and NoSQL databases (e.g., MongoDB).

• Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and their data services.

• Strong understanding of data modeling, data warehousing, and data lake architectures.

• Experience with geospatial data integration and visualization tools (e.g., ArcGIS, QGIS).

• Knowledge of data governance, data quality, and metadata management best practices.

• Understanding of data security, encryption, and compliance standards (e.g., HIPAA, FedRAMP).

• Excellent problem-solving and communication skills.

• Preferred certifications: Google Cloud Professional Data Engineer, AWS Certified Data Analytics, or Microsoft Azure Data Engineer Associate.

CIYIS is an Equal Opportunity Employer and all Qualified Applicants will receive consideration for employment without regard to Race, Color, Religion, Sex, National Origin, Disability Status, Protected Veteran Status or any other Characteristic Protected by Law.