Senior Enterprise Data Architect — Lead Data Solutions

Jobtome; Greenwood Village (CO); On-site; USD 111,000 - 196,000; Full time

Job summary

Spectrum is seeking a Principal Data Architect I to architect and lead advanced data engineering initiatives that empower enterprise intelligence. You will mentor teams and steer end-to-end data solutions across platforms and locations in a dynamic, US-based environment.

Responsibilities include building scalable data structures, ETL processes, and monitoring data warehouses. A strong background in SQL, Python, and data visualization tools is essential.

Qualifications

• Bachelor's degree or equivalent experience required.
• 5+ years data integration and 8+ years ETL experience preferred.
• Experience with SQL, Python, JSON, and data warehousing concepts required.

Responsibilities

• Architect data structures, models, and movement infrastructures for enterprise data warehousing and MDM.
• Lead deployment of data services, optimize error handling, data manipulation, and I/O processing.
• Design and monitor requirements and architecture for data warehousing and processing systems.
• Direct Insights team to deliver end-to-end data solutions across platforms and locations.
• Oversee ETL development and data integration aligned with Spectrum standards.

Skills

ETL

SQL

Shell scripting

Python

JSON

Data integration

Tableau

Alterx

MicroStrategy

Software engineering

English

Data lake

Data warehousing

SQL/Hive

Web services

FTP/sFTP

ETL processing

Communication

Troubleshooting

Education

Bachelor's degree or equivalent experience

Master's degree or equivalent experience

Tools

Tableau

Alterx

MicroStrategy

WSDL/SOAP

RESTful

Job description

Spectrum is seeking a Principal Data Architect I to architect and lead advanced data engineering initiatives that empower enterprise intelligence. You will mentor teams and steer end-to-end data solutions across platforms and locations in a dynamic, US-based environment.

Responsibilities include building scalable data structures, ETL processes, and monitoring data warehouses. A strong background in SQL, Python, and data visualization tools is essential.