Enterprise Data Architect

Enterprise Data Architect

Location: Fully Remote (U.S. – Eastern or Central Time Zones Preferred)

Type: 6-Month Contract-to-Hire

Compensation Upon Conversion: $150,000–$175,000 Base Salary

Overview

We are seeking an experienced Enterprise Data Architect to lead the design, implementation, and evolution of enterprise-scale data architecture initiatives. This individual will play a key role in shaping data strategy, modernizing data platforms, leading complex data migration efforts, and enabling analytics and business intelligence capabilities across the organization.

The ideal candidate brings deep expertise in cloud-based data architectures, data modeling, governance, integration, and modern Lakehouse technologies. This is a highly visible role that partners with business and technology leaders to ensure data is trusted, scalable, secure, and aligned with strategic business objectives.

What You'll Do

Enterprise Data Strategy & Architecture

• Develop and execute enterprise data architecture strategies aligned with business goals.
• Design scalable data models, integration frameworks, and data flows that support operational and analytical workloads.
• Establish architecture standards, best practices, and governance frameworks.
• Evaluate and recommend technologies that support long-term data management and analytics objectives.

Data Migration Leadership

• Lead large-scale data migration initiatives from discovery through production cutover.
• Define migration strategies, mapping rules, transformation logic, and validation processes.
• Oversee data cleansing, enrichment, reconciliation, and testing efforts.
• Design and govern migration pipelines and technical architecture.

Data Governance & Quality

• Implement data governance, metadata management, and master data management strategies.
• Establish data quality standards, monitoring processes, and performance metrics.
• Ensure compliance with security, privacy, and regulatory requirements.
• Drive data lineage, cataloging, and impact analysis initiatives.

Modern Data Platform & Lakehouse Architecture

• Design and implement Lakehouse architectures supporting both structured and unstructured data.
• Evaluate and leverage technologies such as Microsoft Fabric, Databricks, Delta Lake, Apache Iceberg, and Apache Hudi.
• Optimize data storage, processing, and analytics performance across cloud platforms.

Business Intelligence & Analytics

• Architect data solutions that support reporting, analytics, and executive decision-making.
• Collaborate with BI teams to develop scalable data models and analytical frameworks.
• Evaluate and recommend modern BI and visualization platforms.

Leadership & Collaboration

• Partner with executive stakeholders, business leaders, and technical teams.
• Lead cross-functional data initiatives and architectural decision-making.
• Mentor architects, engineers, and data management professionals.
• Communicate complex technical concepts to both technical and non-technical audiences.

Required Qualifications

• 10 years of experience in data architecture, data engineering, or enterprise data management.
• Expertise in advanced SQL and enterprise data modeling.
• Strong experience designing cloud-based data platforms.
• Deep understanding of ETL/ELT frameworks and enterprise data integration.
• Experience implementing data governance, security, and compliance frameworks.
• Proven success leading enterprise-scale data migration initiatives.
• Strong communication, leadership, and stakeholder management skills.

Technical Expertise

Data Architecture & Modeling

• Conceptual, logical, and physical data modeling
• Dimensional modeling (star and snowflake schemas)
• Data Vault methodologies
• Master Data Management (MDM)
• Data modeling tools such as ERwin, ER/Studio, Lucidchart, or similar

Cloud Data Platforms

Experience with one or more major cloud ecosystems:

• Microsoft Azure (Fabric, Synapse, Data Factory)
• AWS (Redshift, Glue, Lake Formation)
• Google Cloud Platform (BigQuery, Dataflow)

Data Integration & Engineering

• ETL/ELT design patterns
• Change Data Capture (CDC)
• API-based integrations
• Batch and real-time data processing
• Event-driven architectures (Kafka, Event Hubs)
• Tools such as dbt, Airflow, Azure Data Factory, Spark, Python, or similar

Databases & Storage

• SQL Server, Oracle, PostgreSQL
• NoSQL platforms such as MongoDB, Cassandra, and DynamoDB
• Data warehouse, data lake, and Lakehouse architectures
• Performance tuning, partitioning, indexing, and query optimization

Governance, Security & Compliance

• Metadata management and data lineage
• Data catalog platforms (Purview, Collibra, Alation, etc.)
• Data security, encryption, RBAC/ABAC, masking, and tokenization
• Regulatory compliance including GDPR, HIPAA, and related frameworks

Preferred Experience

Candidates with experience in the following areas will stand out:

• Real-time and event-driven architectures
• DataOps and automation practices
• Data Mesh, Data Fabric, and modern architectural patterns
• Data observability platforms such as Monte Carlo or Great Expectations
• AI/ML data infrastructure and pipelines
• Feature stores, graph databases, and knowledge graphs
• Infrastructure as Code (Terraform, ARM Templates)
• CI/CD for data platforms using Azure DevOps or GitHub Actions

Why This Opportunity?

This role offers the chance to influence enterprise-wide data strategy, drive modernization efforts, and build scalable data solutions that directly impact business performance. You'll work alongside senior leaders and technical experts while helping shape the future of the organization's data ecosystem.