Lead Data Architect / DTAM / (Hybrid) [Contingent]

The Lead Data Architect serves as the senior technical authority responsible for defining the enterprise data architecture, database platforms, data engineering standards, and data integration strategy for the Decennial Transformation and Application Modernization (DTAM) program. This role provides technical leadership for modernizing enterprise data platforms and ensuring secure, scalable, and high-performing data ecosystems that support mission-critical Census operations.

This role owns the architecture and technical direction for enterprise databases, data warehouses, data lakes, ETL/ELT pipelines, metadata management, and data governance., 1. Serve as the technical lead responsible for enterprise data architecture, database standards, and data engineering strategy across the DTAM program.

1. Define the architecture, standards, and governance for enterprise data platforms including relational databases, data warehouses, and enterprise data lakes.
2. Lead the design and modernization of enterprise data architectures supporting cloud, hybrid, and on-premise environments.
3. Architect and oversee scalable ETL/ELT pipelines, enterprise data integration solutions, and high-volume data processing workflows.
4. Lead database architecture and optimization across Oracle, PostgreSQL, Amazon Aurora, Amazon Redshift, and enterprise data lake environments.
5. Define enterprise standards for SQL, PL/SQL, database performance, data modeling, metadata management, and data lifecycle management.
6. Establish enterprise data governance practices including data quality, lineage, metadata, master data management, retention, and compliance.
7. Collaborate with the Lead Application Architect and Lead Application Developers to integrate enterprise applications with data platforms and APIs.
8. Partner with the Lead Data Scientists to deliver trusted, high-quality data supporting analytics, reporting, AI/ML, and decision-support capabilities.
9. Work with the Lead Systems Architect to ensure data platforms align with enterprise cloud architecture and infrastructure standards.
10. Partner with the Lead Security Engineer to implement secure data architectures that satisfy federal security, privacy, and compliance requirements.
11. Evaluate emerging database technologies, integration approaches, and modernization strategies to improve scalability, reliability, and operational efficiency.
12. Produce architecture documentation, logical and physical data models, technical standards, and implementation guidance.
13. Provide technical leadership, mentoring, and architectural oversight across multiple concurrent projects and engineering teams.

• 10-14 years of experience in enterprise data architecture, database architecture, data engineering, or related technical disciplines.
• Demonstrated experience leading enterprise-scale data modernization or database architecture initiatives.
• Deep expertise designing enterprise data architectures supporting relational databases, data warehouses, enterprise data lakes, and modern data platforms.
• Experience designing and implementing enterprise ETL/ELT pipelines and large-scale data integration architectures.
• Strong experience with Oracle, PostgreSQL, Amazon Aurora, Amazon Redshift, or comparable enterprise database technologies.
• Strong SQL and PL/SQL development and database optimization experience.
• Experience with enterprise data governance including metadata management, data lineage, data quality, master data management (MDM), and lifecycle governance.
• Experience integrating enterprise applications through APIs, data services, and data integration platforms.
• Experience supporting cloud, hybrid, and on-premise enterprise data environments.
• Ability to produce enterprise architecture documentation, data models, technical standards, and implementation guidance.
• Strong communication and leadership skills with experience collaborating across architecture, engineering, analytics, and security teams.

Preferred Qualifications:

• Certifications:
• AWS Data Analytics or Machine Learning Certifications
• Microsoft Azure Data Engineer or AI certifications
• Google Cloud Data Analytics or Professional Data Engineer certification
• Experience supporting federal government or large-scale mission-driven programs
• Exposure to AI/ML technologies including generative AI and large language models
• Experience with data privacy and security approaches (e.g., federated learning, differential privacy)

Please Note: We maintain an on-camera policy for all virtual company meetings to foster engagement and collaboration. Reasonable exceptions may be granted with prior approval from Human Resources and/or the applicable manager or client.

We offer exceptional comprehensive benefits (Medical, Dental, Vision, Life and Disability); 401(k); Health and Wellness Benefits; and Paid Sick Time, Vacation Time, and Holiday Time. You’re eligible for bonuses throughout the year as part of our incentive program for innovation and business development. All employees are also considered for an annual raise, commensurate with performance and company commitment., Salary Range: $130K - $165K - (commensurate with the candidate’s skills, experience, location, and qualifications)

iWorks Corporation, founded in 2005, is a leading provider of information technology and professional services to the federal government. We are a recognized leader in personnel security and vetting solutions, Agile, DevOps, DevSecOps, data analytics, and cloud solutions. Our continuous process improvement approach, combined with our business and technology expertise, results in innovative solutions., iWorks is committed to maintaining a safe and productive work environment for all employees and ensuring the security and well-being of our clients. As part of our standard hiring process, we may conduct background checks and drug screenings on potential candidates to assess their suitability for employment.