Location / Remote: Hybrid in Cleveland, OH, 44143 (3 days per week onsite).
Employment Type: 6-month W-2 contract (possibility to extend)
Compensation: up to 100/hour W-2 (depending on experience).
Benefits: Medical, dental, vision, LTD/STD, HSA/FSA, term life, and supplemental health insurances (e.g., Aflac) for all employees (and their families if needed).
The Data Architect (Hands-On) will play a pivotal role in designing, stabilizing, and governing enterprise data platforms and flows across distributed systems. This position combines architectural leadership with hands-on engineering to ensure data quality, scalable enterprise data models, and reliable data propagation. The ideal candidate will have deep expertise in Azure data platforms, advanced SQL, and data governance frameworks, along with the ability to directly analyze production data and resolve integrity issues.
Responsibilities:
Design and implement enterprise data architecture and canonical data models.
Define data ownership, governance rules, and data quality standards.
Analyze and stabilize data pipelines and cross-platform data propagation.
Perform hands-on SQL analysis and data reconciliation across enterprise systems.
Implement data validation, monitoring, and data quality frameworks.
Collaborate closely with engineering teams to align data architecture with platform and integration services.
Diagnose and resolve data integrity issues in production environments.
Improve data observability, lineage tracking, and governance processes.
Leverage AI-driven analytics and automation to identify anomalies and accelerate analysis.
Required Skills:
8 10+ years of experience in data architecture or data engineering.
Expertise in enterprise data architecture and data modeling.
Advanced SQL and data analysis capabilities.
Proficiency with Azure data platform services, including Azure Data Factory and Azure SQL/Synapse.
Experience with event-driven and distributed data systems.
Strong knowledge of data governance and data quality frameworks.
Proven ability to analyze production data and resolve data integrity issues.
Hands-on experience designing enterprise data models and distributed platforms.
Direct experience with cloud-based data platforms.
Preferred Skills:
Experience with AI-assisted analytics or automation tools.
Ability to leverage AI-driven analytics to identify anomalies and accelerate analysis.
Familiarity with improving data observability, lineage tracking, and governance processes.
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