Data Architect

About Capital Technology Alliance:

At Capital Technology Alliance, we believe changing the future of technology means valuing people. We are committed to building a collaborative, high-performing environment where professionals are empowered to deliver meaningful impact. Our teams work on challenging, often high-visibility initiatives that support mission-critical systems, enterprise modernization efforts, and data-driven decision-making.

CTA is proud to demonstrate a high renewal rate with our employees and contractors. We place a high value on expertise. That’s why CTA is committed to paying top rates in the industry and connecting you with positions and flexible engagement options that match your skills and professional goals.

Job Overview:

The Data Architects will serve on the Data Warehouse Team Modernization Project. The roles drive enterprise-wide data design, ensuring optimized data structures that balance accessibility, performance, and resource utilization. The Data Architects will focus on developing comprehensive logical and physical data models, defining source-to-target mappings, and establishing robust data quality and lineage standards. These roles provide strategic guidance on data architecture best practices, establish organizational standards for data structures and metadata, and support the design of data acquisition, integration, and database-optimization strategies to enable reliable, scalable, and governed data solutions across the enterprise.

Job Duties:

Enterprise Data Architecture and Modeling

• Define and maintain enterprise-wide logical and physical data models, ensuring alignment with organizational standards and future scalability
• Develop and document source-to-target mappings that support data integration, transformation, and reporting needs
• Design and optimize data architectures, including Operational Data Stores (ODS), Data Warehouses, and Data Marts

Data Standards, Governance, and Quality

• Establish and enforce data architecture standards, policies, and procedures for data structures, naming conventions, metadata management, and reference data
• Define and maintain rigorous data quality rules to ensure the accuracy, consistency, completeness, and reliability of all enterprise data assets
• Document and maintain data lineage, capturing end-to-end data flows, business rules, and transformation logic

Data Acquisition, Analysis, and Optimization

• Collaborate with Data Warehouse Analysts to understand data requirements, usage patterns, and integration points across systems
• Lead data acquisition and access analysis, defining strategies for ingestion, transformation, and distribution
• Provide expertise in Database Management System (DBMS) optimization, including performance tuning, indexing strategies, and resource utilization
• Design and support batch loading strategies, ensuring efficient data movement, error handling, and recovery procedures

Architecture Guidance and Project Support

• Act as a Subject Matter Expert (SME) for data architecture best practices, advising teams on modeling, integration patterns, and technology selection
• Apply and promote accepted data content standards across technology projects to ensure consistency and interoperability
• Partner with developers, analysts, and stakeholders to ensure data solutions align with enterprise goals and meet functional and non-functional requirements

Documentation, Compliance, and Continuous Improvement

• Produce clear documentation for models, mappings, lineage, and standards to support knowledge transfer and audit readiness
• Support compliance with regulatory, security, and privacy standards by implementing data governance controls and traceability
• Continuously assess and enhance data

Required Qualifications:

• A minimum of seven (7) years of experience in Extract, Transform, Load (ETL) development and data engineering
• A minimum of three (3) years of hands-on experience working with Azure Data Factory (ADF), Azure Databricks, Azure Synapse Analytics, and Azure Purview
• Proven track record of building and optimizing large-scale ETL pipelines for high-performance, high-availability environments
• Expertise in Spark, Python, or Scala for large-scale data transformations
• Strong in Structured Query Language (SQL) proficiency and experience working with complex data structures
• Comprehensive knowledge of data governance, security protocols, and Role-Based Access Control (RBAC) within the Azure ecosystem
• Ability to design ETL processes that are resilient, efficient, and fully compliant with regulatory standards

Preferred Qualifications:

• Experience managing Amazon Web Services (AWS) warehouse, AWS S3, and Data Sync processes.
• Comprehensive understanding of Criminal Justice Information (CJI), Health Insurance Portability and Accountability Act (HIPAA), and Personally Identifiable Information (PII) compliance knowledge.
• Possesses Microsoft certifications in Azure Data Engineer Associate, Azure Solutions Architect Expert, and Azure Fundamentals.
• Possesses a Databricks Certification as a Data Engineer Associate.

Education:

• A bachelor’s degree from an accredited college or university in Computer Science, Information Systems, or other related field, or equivalent work experience in Service-Oriented Architecture (SOA) and Azure Cloud Solutions will be considered