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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Lead Data Architect / DTAM / (Hybrid) [Contingent] - **Company:** iWorks Corporation - **Location:** United States - **Experience:** Expert - **Salary:** $130,000.0 - $165,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Applications Architecture, Microsoft Azure, Big Data, Cloud Computing, Databases, Data as a Services, Data Architecture, Information Engineering, Data Governance, Data Infrastructure, Data Integration, Extract Transform Load (ETL), Data Transformation, Data Security, Dataspaces, Data Warehousing, Relational Databases, Information Lifecycle Management, PostgreSQL, Machine Learning, Meta-Data Management, Oracle (Applications), Standard Sql, PL-SQL, SQL Databases, Enterprise Data Management, Google Cloud, Enterprise Software Applications, Large Language Models, Database Optimization, Database Performance, Data Lakes, Data Lineage, Data Analytics, AWS Data Analytics, Data Management, Data Pipelines, Amazon Redshift - **Published:** July 30, 2026 - **Apply:** https://www.clearancejobs.com/jobs/9068711/lead-data-architect-dtam-hybrid-contingent ## About the Role * 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. ## Description 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. 2. Define the architecture, standards, and governance for enterprise data platforms including relational databases, data warehouses, and enterprise data lakes. 3. Lead the design and modernization of enterprise data architectures supporting cloud, hybrid, and on-premise environments. 4. Architect and oversee scalable ETL/ELT pipelines, enterprise data integration solutions, and high-volume data processing workflows. 5. Lead database architecture and optimization across Oracle, PostgreSQL, Amazon Aurora, Amazon Redshift, and enterprise data lake environments. 6. Define enterprise standards for SQL, PL/SQL, database performance, data modeling, metadata management, and data lifecycle management. 7. Establish enterprise data governance practices including data quality, lineage, metadata, master data management, retention, and compliance. 8. Collaborate with the Lead Application Architect and Lead Application Developers to integrate enterprise applications with data platforms and APIs. 9. Partner with the Lead Data Scientists to deliver trusted, high-quality data supporting analytics, reporting, AI/ML, and decision-support capabilities. 10. Work with the Lead Systems Architect to ensure data platforms align with enterprise cloud architecture and infrastructure standards. 11. Partner with the Lead Security Engineer to implement secure data architectures that satisfy federal security, privacy, and compliance requirements. 12. Evaluate emerging database technologies, integration approaches, and modernization strategies to improve scalability, reliability, and operational efficiency. 13. Produce architecture documentation, logical and physical data models, technical standards, and implementation guidance. 14. Provide technical leadership, mentoring, and architectural oversight across multiple concurrent projects and engineering teams. ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [Kubernetes and Microservices with Multi-Model Databases](https://www.wearedevelopers.com/videos/382-kubernetes-and-microservices-with-multi-model-databases) - [Fault Tolerance and Consistency at Scale: Harnessing the Power of Distributed SQL Databases](https://www.wearedevelopers.com/videos/1146-fault-tolerance-and-consistency-at-scale-harnessing-the-power-of-distributed-sql-databases) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Dev Digest 132 - Binging WADFlix?](https://www.wearedevelopers.com/magazine/473-dev-digest-132-binging-wadflix) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline) - [Best US AI Conferences for CTOs in 2026: Build vs. Buy, Vendor Evaluation, and Peer Intelligence](https://www.wearedevelopers.com/magazine/736-best-us-ai-conferences-for-ctos-in-2026-build-vs-buy-vendor-evaluation-and-peer-intelligence)