**Please strictly adhere to the following resume naming convention:
ALL CAPS, NO SPACES BETWEEN UNDERSCORES
PTN_US_GBAMSREQID_CandidateBeelineID
Example: PTN_US_9999999_SKIPJOHNSON0413
: -
MSP Owner: Michelle Lee
Location: Bentonville, AR
Duration: 6 months
skill id: 10679815
Role Overview
The Data Architect is responsible for designing, creating, deploying, and managing an organization's data architecture. This role ensures that data is structured, stored, integrated, secured, and governed in a way that supports business strategy, analytics, regulatory requirements, and scalability.
The Data Architect works closely with business stakeholders, solution architects, data engineers, and application teams to translate business requirements into robust data solutions.
Key Responsibilities
Data Architecture & Design
• Define and maintain enterprise and solution-level data architecture aligned to business and IT strategy.
• Design logical, physical, and conceptual data models for transactional and analytical systems.
• Establish standards for data integration, storage, quality, metadata, and lifecycle management.
• Design architectures for data warehouses, data lakes, lakehouses, and real-time data platforms.
Cloud & Platform Architecture
• Architect data solutions on cloud platforms such as Azure, AWS, or GCP.
• Select and design appropriate technologies for:
o Data ingestion (batch & streaming)
o Storage (relational, NoSQL, columnar, object storage)
o Processing and analytics
• Optimize solutions for performance, scalability, cost, and resiliency.
Data Governance, Security & Compliance
• Define and enforce data governance frameworks, including:
o Data ownership and stewardship
o Master data and reference data management
o Metadata management
• Ensure compliance with data privacy and regulatory requirements (e.g., GDPR, HIPAA, SOX, local regulations).
• Design data security controls including encryption, masking, access control, and auditing.
Collaboration & Stakeholder Management
• Collaborate with business leaders, product owners, data engineers, BI teams, and developers.
• Translate business requirements into architectural blueprints and data solutions.
• Review and approve data designs and implementations for alignment with standards.
Modernization & Innovation
• Lead data modernization initiatives (legacy to cloud, monolith to modular).
• Evaluate emerging technologies and recommend adoption where beneficial.
• Support advanced analytics, AI/ML, and self service BI use cases.
Required Skills & Qualifications
Technical Skills
• Strong experience in data modeling (ER, dimensional, Data Vault).
• Expertise in RDBMS and NoSQL technologies (e.g., Oracle, SQL Server, PostgreSQL, MongoDB, Cassandra).
• Hands on knowledge of data warehousing and big data ecosystems.
• Experience with ETL/ELT and data integration tools.
• Solid understanding of:
o SQL and data optimization
o APIs and data services
o Streaming platforms (e.g., Kafka - optional but preferred)
Cloud & Tools (Any combination)
• Azure: Synapse, Data Factory, Databricks, Purview
• AWS: Redshift, Glue, Athena, Lake Formation
• GCP: BigQuery, Dataflow, Dataproc
Architecture & Methodologies
• Strong grounding in enterprise architecture principles.
• Familiarity with TOGAF or similar frameworks (preferred).
• Experience working in Agile / DevOps environments.
Skills: Data Architecture and Modeling
Experience Required: 6-8, Project Code :
ALL CAPS, NO SPACES BETWEEN UNDERSCORES
PTN_US_GBAMSREQID_CandidateBeelineID
Example: PTN_US_9999999_SKIPJOHNSON0413
: -
MSP Owner: Michelle Lee
Location: Bentonville, AR
Duration: 6 months
skill id: 10679815
Role Overview
The Data Architect is responsible for designing, creating, deploying, and managing an organization's data architecture. This role ensures that data is structured, stored, integrated, secured, and governed in a way that supports business strategy, analytics, regulatory requirements, and scalability.
The Data Architect works closely with business stakeholders, solution architects, data engineers, and application teams to translate business requirements into robust data solutions.
Key Responsibilities
Data Architecture & Design
• Define and maintain enterprise and solution-level data architecture aligned to business and IT strategy.
• Design logical, physical, and conceptual data models for transactional and analytical systems.
• Establish standards for data integration, storage, quality, metadata, and lifecycle management.
• Design architectures for data warehouses, data lakes, lakehouses, and real-time data platforms.
Cloud & Platform Architecture
• Architect data solutions on cloud platforms such as Azure, AWS, or GCP.
• Select and design appropriate technologies for:
o Data ingestion (batch & streaming)
o Storage (relational, NoSQL, columnar, object storage)
o Processing and analytics
• Optimize solutions for performance, scalability, cost, and resiliency.
Data Governance, Security & Compliance
• Define and enforce data governance frameworks, including:
o Data ownership and stewardship
o Master data and reference data management
o Metadata management
• Ensure compliance with data privacy and regulatory requirements (e.g., GDPR, HIPAA, SOX, local regulations).
• Design data security controls including encryption, masking, access control, and auditing.
Collaboration & Stakeholder Management
• Collaborate with business leaders, product owners, data engineers, BI teams, and developers.
• Translate business requirements into architectural blueprints and data solutions.
• Review and approve data designs and implementations for alignment with standards.
Modernization & Innovation
• Lead data modernization initiatives (legacy to cloud, monolith to modular).
• Evaluate emerging technologies and recommend adoption where beneficial.
• Support advanced analytics, AI/ML, and self service BI use cases.
Required Skills & Qualifications
Technical Skills
• Strong experience in data modeling (ER, dimensional, Data Vault).
• Expertise in RDBMS and NoSQL technologies (e.g., Oracle, SQL Server, PostgreSQL, MongoDB, Cassandra).
• Hands on knowledge of data warehousing and big data ecosystems.
• Experience with ETL/ELT and data integration tools.
• Solid understanding of:
o SQL and data optimization
o APIs and data services
o Streaming platforms (e.g., Kafka - optional but preferred)
Cloud & Tools (Any combination)
• Azure: Synapse, Data Factory, Databricks, Purview
• AWS: Redshift, Glue, Athena, Lake Formation
• GCP: BigQuery, Dataflow, Dataproc
Architecture & Methodologies
• Strong grounding in enterprise architecture principles.
• Familiarity with TOGAF or similar frameworks (preferred).
• Experience working in Agile / DevOps environments.
Skills: Data Architecture and Modeling
Experience Required: 6-8, Project Code :