Hybrid Opportunity || Data Architect || Newark, NJ || Contract

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Job Title: Data Architect

Location: Newark, NJ- Hybrid

Mode of Hire: Contract

Job Description:

:

Define enterprise data architecture standards, create data exchange and ingestion frameworks, establish data quality and governance patterns, and develop data domain models and templates that ensure consistent, high-quality data across the organization. This role creates enterprise data patterns and frameworks, not operational data solutions.

• Data framework architect: Design the data ingestion framework with schema validation, quality checks, and exception handling used enterprise-wide
• Data quality champion: Embed quality into frameworks at ingestion, not as afterthought
• Exchange pattern owner: Create the patterns for internal and third-party data exchange
• Strategic partnership: Collaborate closely with Data Platform Enablement team (they operate the platform, you create the patterns)
  
  

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Enterprise Data Standards & Patterns (40%)

• Help define enterprise data modeling standards (conceptual, logical, physical, dimensional models)
• Create data domain model standards with quality framework integration
• Define data architecture patterns for common scenarios (OLTP, OLAP, streaming, hybrid)
• Document data persistence patterns (SQL vs NoSQL selection, data lake vs warehouse, caching)
• Create master data management patterns and reference data standards
• Establish data lifecycle management standards (retention, archival, purging)
  
  

Data Exchange & Ingestion Frameworks (35%)

Design enterprise data ingestion framework:

• Central pipeline architecture for all data ingestion (batch, streaming, real-time)
• Schema validation framework (enforce schemas at ingestion, schema registry)
• Data quality validation framework integrated into pipeline (completeness, accuracy, consistency, timeliness)
• Exception handling framework (quarantine, alerts, remediation workflows)
• Data lineage tracking through ingestion pipeline
  
  

Create data exchange patterns for:

• Internal system-to-system data sharing
• Third-party data exchange (inbound/outbound): SFTP/API patterns, data format standards, partner onboarding templates, data contract templates
• Real-time vs batch exchange criteria
  
  

Additional responsibilities:

• Define data integration patterns (ETL, ELT, streaming, CDC, data virtualization)
• Establish data API standards (data services, data APIs vs transactional APIs)
  
  

Data Quality & Governance Frameworks (15%)

• Create enterprise data quality framework (quality dimensions, metrics, rules by domain, monitoring, remediation)
• Define data governance patterns (stewardship model, cataloging standards, metadata management, lineage and impact analysis)
• Establish data privacy and protection patterns (PII handling, encryption, masking, tokenization)
• Document data classification framework (public, internal, confidential, restricted)
  
  

Roadmap & Enablement (10%)

• Develop enterprise data architecture modernization roadmap
• Train solution architects on data patterns and frameworks
• Review solution architectures for data pattern compliance
• Coordinate with Data Platform Enablement team on platform capabilities vs patterns
• Participate in data governance forums
  
  

Education:

• Bachelor's degree in computer science, Information Systems, Data Science, or related field
  
  

Experience:

• 12 years in data architecture, data engineering, or enterprise architecture
• 5 years creating enterprise data standards, frameworks, and patterns
• Proven experience designing data ingestion frameworks with quality and governance
• Experience with data exchange patterns for internal and external parties
• Track record establishing canonical data models and data governance frameworks
  
  

Certifications (Preferred):

• TOGAF certification
• Cloud data platform certification (AWS Data Analytics, Azure Data Engineer, Google Cloud Data Engineer)
• DAMA CDMP (Certified Data Management Professional)
• Data governance certification
  
  

Preferred Qualifications:

Experience in healthcare or financial services with complex data exchange requirements

Track record implementing data quality frameworks at enterprise scale

Experience with third-party data exchange and partner onboarding

Published thought leadership on data architecture or data quality

Experience with data privacy regulations (HIPAA, GDPR, CCPA)

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