Data Architect

Insight Global
Salt Lake City, UT, United States
1 day ago
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Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours

Tech stack

Artificial Intelligence Business Analytics Applications Data Analysis Information Systems Data Architecture Information Engineering Data Governance Data Infrastructure Extract Transform Load (ETL) Data Warehousing Supervisory Control and Data Acquisition (SCADA) Python (Programming Language)
+6 more
Operational Data Store Cloud Services SQL Databases SC Clearance Data Lakes Information Technology

Job description

Insight Global is looking for a Data Architect to design, build, and maintain scalable data solutions that support manufacturing, operations, analytics, and AI initiatives. This individual will be responsible for improving data quality, developing data models and pipelines, and ensuring operational data is structured, accessible, and actionable for business decision-making. This role will be located onsite in Salt Lake City and will be a 12 month contract with opportunity for full-time conversion.

Requirements

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

-5+ years of experience in data architecture, data engineering, database management, or related fields.

-Strong proficiency with SQL, Python, and data modeling concepts.

-Experience with data warehouses, data lakes, ETL/ELT processes, and cloud data platforms.

-Knowledge of data governance, data quality management, and analytics best practices.

-Ability to translate complex operational data into meaningful business insights. -Experience supporting manufacturing, aerospace, defense, or industrial operations.

-Familiarity with PLC, SCADA, MES, or other operational technology systems.

-Experience with AI/ML data environments and analytics platforms.

-Active Secret Clearance or ability to obtain one.

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Good distractions

Talks and stories from around this role — technically off-topic, practically not.

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The governance failures of centralized data lakes

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Automating exploratory data analysis within training pipelines

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Structuring career paths and localized data architectures

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Distributed data lakes and containerized computing clusters

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Performing exploratory data analysis to uncover underlying patterns

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