> Markdown version of [/jobs/ext/1785425-data-infrastructure-architect](https://www.wearedevelopers.com/jobs/ext/1785425-data-infrastructure-architect). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Infrastructure Architect - **Company:** City of New York - **Location:** New York, NY, United States - **Experience:** Experienced - **Salary:** $68,213.0 - $140,000.0 - **Contract:** Permanent contract - **Skills:** Query Performance, Big Data, Databases, Data Architecture, Data Governance, Data Infrastructure, Data Integration, Data Integrity, Extract Transform Load (ETL), Data Normalization, Data Security, Dataspaces, Data Structures, Data Systems, Data Warehousing, Database Schema, Digital Assets, Document-Oriented Databases, Identity and Access Management, Python (Programming Language), Meta-Data Management, Cloud Services, SQL Databases, Data Streaming, Unstructured Data, Enterprise Data Management, Scripting, Data Storage Technologies, Data Lakes, Data Management, Physical Data Models - **Published:** July 10, 2026 - **Apply:** https://www.juju.com/job/00000000gfd60y ## About the Role 1. Do you have a baccalaureate degree from an accredited college or university? 2. Do you have an associate degree from an accredited college or university along with two (2) years of experience with administrative, analytic, coordinative, supervisory or liaison responsibilities? 3. Do you have a four-year high school diploma, or its educational equivalent approved by a state's Department of Education or a recognized accrediting organization along with four (4) years of experience as described in question "2" above? 4. Do you have a satisfactory combination of education and/or experience equivalent to that described in questions "1," "2," and/or "3" above? ## Description The Data Infrastructure Architect will design, implement, and manage MOCJ's data architecture to support secure, scalable, and reliable data access, storage, integration, and analysis. This role will help build and maintain a high-quality data ecosystem by standardizing data structures, improving data flows, supporting data warehousing, and ensuring that agency data assets are secure, consistent, accessible, and usable for analytics, reporting, and decision-making. Responsibilities include but are not limited to: Data Architecture and Modeling - Design conceptual, logical, and physical data models, database schemas, and enterprise data flow structures. - Support the architecture and optimization of transactional databases, data warehouses, data lakes, and large-scale data systems. - Develop scalable frameworks for storing, organizing, and accessing structured and unstructured data. - Document data architectures, system dependencies, data flows, and technical standards. Data Integration, Standardization, and Quality - Develop and maintain frameworks for integrating data from internal and external sources. - Implement data normalization, transformation, and validation workflows using SQL, Python, and other scripting or automation tools. - Support ETL/ELT processes and data quality controls to ensure reliable, consistent, and analysis-ready datasets. - Monitor data quality, resolve inconsistencies, and recommend improvements to strengthen the agency's data ecosystem. Governance, Security, and Compliance - Define and support standards for data governance, metadata management, master data, access controls, and regulatory compliance. - Ensure data assets are managed in accordance with applicable privacy, security, and compliance requirements. - Partner with IT, legal, program, and research teams to support secure and appropriate use of agency data. - Recommend tools, processes, and controls to strengthen data security, access management, and data integrity. Technical Strategy and Implementation - Evaluate and recommend database platforms, storage solutions, cloud services, and data technologies that support agency needs. - Plan and support deployments, migrations, and modernization of data systems. - Monitor query performance, pipeline efficiency, system scalability, and data storage practices. - Optimize ETL pipelines, normalization scripts, data structures, and automated data processes. Cross-Functional Coordination - Work with internal and external data engineers, analysts, IT staff, program teams, and agency leadership to translate business needs into technical solutions. - Provide guidance on data modeling, normalization, governance, and system design. - Manage data infrastructure projects, timelines, resources, risks, and deliverables. - Stay current on emerging technologies and best practices in data architecture, automation, cloud data platforms, and data quality management. ## 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) - [JavaScript? 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