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# Senior Data Architect

- **Company:** NuAxis Innovations
- **Location:** United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Data Analysis, Application Integration Architecture, Microsoft Azure, Cloud Database, Data Architecture, Data Governance, Data Infrastructure, Extract Transform Load (ETL), Data Security, Data Vault Modeling, Python (Programming Language), Metadata, Cloud Services, Data Mesh, SQL Databases, Data Streaming, Talend, Snowflake, Togaf, Information Technology, Collibra, AWS Glue, Data Analytics, Apache Kafka, Operational Systems, Data Management, Azure Synapse Analytics, Amazon Redshift, Databricks
- **Published:** October 9, 2026
- **Apply:** https://www.clearancejobs.com/jobs/9229762/senior-data-architect

## About the Role

· Minimum Education: Bachelor's degree in Computer Science, Information Technology, or a related field.

· Minimum Experience: Eight (8) or more years of data architecture experience. This position carries a Lead-equivalent experience floor given its cross-platform design authority.

· Certifications - Required: Cloud data or architecture certification (e.g., AWS Certified Data Analytics - Specialty, Microsoft Certified Azure Data Engineer Associate, or SnowPro Advanced: Architect).

· Certifications - Obtainable After Hire: TOGAF 9/10 Certified, within 180 days of assignment.

· Certifications - Preferred: DAMA Certified Data Management Professional (CDMP); Collibra Ranger; Databricks Certified Data Engineer Professional.

· Required Skills: Data modeling; ETL and ELT design; cloud data platforms; data governance frameworks; metadata and lineage; integration architecture; data security and privacy patterns.

· Preferred Skills: Snowflake and modern lakehouse architectures; data mesh and data product approaches; analytics enablement; federal data environments.
Technical Environment

erwin Data Modeler or ER/Studio; Snowflake, Amazon Redshift, Azure Synapse, and Databricks; dbt; Informatica, Talend, or AWS Glue; Apache Kafka and event streaming; Collibra or Alation for catalog and lineage; SQL and Python; Kimball, Inmon, and Data Vault 2.0 modeling patterns; Microsoft Purview; NIST and privacy control alignment

## Description

Designs and manages enterprise data architecture, models, governance, and integration patterns so data is accurate, accessible, secure, and useful for analytics and applications.
Key Responsibilities

· Define enterprise data architecture, conceptual, logical, and physical models, and data domain standards.

· Design ETL and ELT integration patterns across operational systems, data platforms, and analytics consumers.

· Establish data governance frameworks: stewardship, metadata, lineage, quality rules, and master data management.

· Architect cloud data platform solutions balancing performance, scalability, security, and cost.

· Define data security, classification, retention, and privacy control patterns.

· Review and approve data designs produced by engineering and BI teams; mentor data practitioners.