Data Governance Lead (Part Time)

DatamanUSA has an exciting opportunity for a Data Governance Lead to work with one of our direct clients in Olympia, WA.



Job Title: Data Governance Lead

Duration: 09 months (with option to extend)

Location: Olympia, WA (Remote)

20 hours per week per role (part-time)

***Remote with on-site availability as needed per program requirements. ***

Required Qualifications:

• Bachelor's Degree including 12 semesters or 18 quarters of computer science coursework.
• Seven (7) years of consultative, administrative, or supervisory experience in IT analysis, data analysis, system maintenance, troubleshooting, or enterprise-level data environments.
• 5+ years of hands-on data-focused leadership (architecture, migration, and/or governance).
• Experience with enterprise data models, flows, governance, metadata, and lineage.
• Experience with data integration, data quality, and migration/conversion patterns.
• Working knowledge of Application Programming Interface (API)-based data services, cloud data tools, and modern platforms.
• Experience with SQL, NoSQL, and cloud data technologies.
• Understanding of regulatory data requirements, privacy standards, and security controls.
• Demonstrated experience leading or contributing to large-scale data migration efforts including profiling, mapping, cleansing, transformation, validation, reconciliation, and conversion readiness.
• Experience with integration patterns such as APIs, ETL/ELT workflows, messaging frameworks, event-driven pipelines, and service-oriented architectures.
• Hands-on experience with cloud ecosystems (Azure, AWS, or Google Cloud Platform), including data storage, processing, serverless functions, and data security controls.
• Familiarity with container platforms (Docker, Kubernetes) as they relate to data processing workloads.
• Proficiency with modern development languages (Java, C#, Python, NodeJS) and associated data manipulation capabilities.
• Experience applying Zero Trust principles, encryption standards, authentication/authorization frameworks, and data security controls across platforms.
• Deep knowledge of data lifecycle management including ingestion, storage, transformation, integration, consumption, archival, retention, and destruction.