Enterprise Architect

DatamanUSA, LLC

Olympia, WA, United States

3 days ago

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Role details

Contract type

Temporary contract

Employment type

Part-time (≤ 32 hours)

Experience level

Expert

Experience required

5 years minimum

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Java (Programming Language) Application Programming Interfaces (APIs) Amazon Web Services Data Analysis Microsoft Azure Big Data C Sharp (Programming Language) Cloud Database Data as a Services Data Architecture Data Governance Data Infrastructure

+27 more

Data Integration Extract Transform Load (ETL) Data Security Information Lifecycle Management Python (Programming Language) Messaging Application Programming Interface Metadata Node.Js NoSQL Zero Trust Network Access Service-Oriented Architecture SQL Databases Enterprise Data Management Privacy Controls Data Processing Google Cloud Data Storage Technologies Cloud Platform System Azure Data Factory Snowflake Containerization Kubernetes Information Technology Cloud Migration Serverless Computing Docker Programming Languages

Requirements

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.