Cloud Data Architect - Data Modeler
New
J
JobgetherIT Consulting / Government
Based in United StatesFull-TimeSenior
Salary169,604 - 229,464 USD per year
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Job Details
- Experience
- 12+ years of general experience and 10+ years of specialized experience, or equivalent combination
- Required Skills
- AWSSnowflakeNosqlData modelingDatabricks
Requirements
- Master's degree in information systems or related field with 12+ years of general experience and 10+ years of specialized experience, or equivalent combinations.
- Extensive experience designing enterprise data architecture using AWS data services.
- Deep expertise in developing scalable, secure operational data models.
- Strong proficiency in relational, NoSQL, and graph database modeling for transaction-intensive environments.
- Hands-on experience with data lakes, lakehouses, and change-data-capture ingestion patterns.
- Proficiency with platforms such as Snowflake, Databricks, or Amazon Redshift.
- Experience with BI tools including Tableau, Power BI, or Amazon QuickSight.
- Strong knowledge of data governance, master data management, and data lineage.
- Experience leading enterprise cloud migration strategies in regulated or government environments.
- Practical understanding of infrastructure-as-code, ETL/ELT, and CI/CD best practices.
- Ability to effectively communicate technical concepts to senior stakeholders.
Responsibilities
- Lead the design, implementation, and continuous improvement of cloud-based data architecture, platforms, and models.
- Architect multi-tenant cloud and hybrid environments, including data lakes, lakehouses, and warehouses.
- Develop and maintain logical, physical, dimensional, and relational data models.
- Define data flows, governance standards, metadata management, and lineage practices.
- Establish integration patterns for ETL/ELT pipelines and secure data APIs.
- Partner with security, governance, and development teams to ensure compliance with federal standards.
- Develop data migration and archival strategies including profiling, validation, and retention scheduling.
- Monitor and optimize database performance through automated tuning and capacity management.
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