Principal Data Architect

(ISR) means being a part of a team committed to discovery and understanding. It means working for the world's largest academic social science survey and research organization, and doing work that really matters to social science in the public interest. The Survey Research Center (SRC) is a collaborative community that conducts cutting-edge research that focus on critical societal issues such as aging, health disparities, and social networks. This position is in the Technical Services Group (TSG) within the Survey Research Operations (SRO ). SRO is the operations branch of the Survey Research Center ( SRC ) at the ISR. At TSG, we are driven by a passion for harnessing technology to build innovative solutions that power the full data collection lifecycle. We are looking for a hands-on Principal Data Architect to lead the team that builds and operates the data pipelines, operational data store, reporting system and data delivery automation behind SRO's survey operations. You will lead and develop a team of data engineers, database administrators, and report developers, set the engineering standards for how data is ingested, transformed, validated, and delivered, and stay close enough to the code to guide design and resolve complex production problems. This position is posted as a Principal Data Architect (Data Architect Staff Specialist), and may be filled at the Data Architect Lead level (see Underfill Statement below). Lead, supervise, and develop a team of data engineers, database administrators, SQL developers, and report developers, including hiring, goal setting, workload management, performance reviews, and career development. Remain hands-on as the team's senior technical contributor: lead design reviews, review pull requests, write and performance-tune T-SQL and Python, and step in on complex production issues. Own production ETL/ELT pipelines that ingest data from 12+ source systems via REST/GraphQL APIs, file-based imports, and operational database extracts, with defined expectations for latency, completeness, and correctness. Own the SQL Server Operational Data Store and its evolution, including near-real-time consolidation for reporting and field operations, infrastructure migration, version road mapping, and extension into a historical data warehouse. Establish data engineering standards and DataOps practices, including source control, code review, CI/CD for database and pipeline code, automated testing, orchestration, monitoring, alerting, and data quality checks. Own and evolve SQLXtend, the team's internal Python data integration framework, and the metadata-driven data services (curated views, stored procedures, data dictionaries, dynamic query definitions, and API-layer structures) that let downstream tools change behavior without code releases. Ensure the security and reliability of data systems that handle sensitive research data, partnering with database administrators on high availability, backups, replication, performance tuning, and SQL Server upgrades in line with University and SRO security standards. Drive technical strategy and delivery with project managers, survey methodologists, and operations stakeholders: prioritize and plan work, manage risk, evaluate tools, ship incrementally, and support reporting platforms such as Power BI Report Server and SSRS. Data Architect Staff Specialist Bachelor's or Master's degree in Computer Science, Information Science, Engineering, or a related field, or an equivalent combination of education and professional experience. 8+ years of professional data engineering experience building and operating production data pipelines, operational data stores, or data warehouses. 5+ years directly supervising data engineers or related technical staff, including hiring, performance reviews, workload management, and building high-performing teams. Expert SQL Server skills, including T-SQL, stored procedures, indexing, query plan analysis, performance tuning, transactional replication, system-versioned temporal tables, and database security. Strong Python skills for data engineering, including consuming REST and GraphQL APIs, handling diverse tabular file formats, and building reusable, testable pipeline code. Experience designing and operating ETL/ELT pipelines with orchestration (e.g., SSIS, Airflow, Dagster, dbt, or equivalent) and strong relational data modeling skills, including integration of heterogeneous source systems. Applied software engineering discipline for data work, including Git, code review, CI/CD, automated testing, and production monitoring and incident response. Ability to translate complex technical concepts into clear guidance for technical and non-technical stakeholders, including survey methodologists, researchers, and project managers. Advanced user of AI-assisted tools such as Claude or GitHub Copilot for coding, testing, and documentation. Data Architect Lead Bachelor's or Master's degree in Computer Science, Information Science, Engineering, or a related field, or an equivalent combination of education and professional experience. 6+ years of professional data engineering experience building and operating production data pipelines, operational data stores, or data warehouses. 3+ years directly supervising data engineers or related technical staff, including hiring, performance reviews, workload management, and building high-performing teams. Demonstrated technical leadership, such as leading projects, running design reviews, mentoring engineers, and communicating clearly with technical and non-technical stakeholders. Advanced SQL Server skills, including T-SQL, stored procedures, indexing, query plan analysis, and performance tuning. Strong Python skills for data engineering, including API-based ingestion, diverse file formats, and reusable, testable pipeline code. Experience designing and operating ETL/ELT pipelines with orchestration and solid relational data modeling skills. Applied software engineering discipline for data work, including Git, code review, CI/CD, and automated testing. Experience supporting reporting platforms such as Power BI Report Server and SSRS. DataOps experience in production, including CI/CD for database code and pipeline code using Azure DevOps, automated data quality testing (e.g., dbt tests, Great Expectations), and pipeline observability alerting using Splunk or comparable tools. Experience building internal data integration frameworks or metadata-driven platforms, such as data dictionaries, configurable schemas, and metadata-controlled validation or transformation. Experience with cloud data and data warehousing platforms (Azure, AWS, or GCP) and with migrating on-premises SQL Server workloads. Monday-Friday, days. This position may be underfilled at the Data Architect Lead level for candidates who meet the Lead qualifications but not all Specialist qualifications. A Lead carries the same technical scope and provides day-to-day technical leadership, work direction, and mentoring for the team. Openings may be filled at the Data Architect Staff Specialist or Data Architect Lead level depending on match with opportunity, your depth and breadth of experience and qualifications. Positions at the Data Architect Staff Specialist level will be filled at the $140,000 - $155,000 salary range. Positions at the Data Architect Staff Lead level will be filled at the $108,000 - $120,000 salary range. The Institute for Social Research (ISR) at the University of Michigan seeks to create a community of respect and authentic collaboration by recruiting and retaining individuals that represent a variety of voices as a reflection of our commitment to serve the people of Michigan, to maintain the excellence of the university, and to ground our research in varied disciplines, perspectives, and ways of knowing and learning. Benefits In addition to a career filled with purpose and opportunity, U-M offers a comprehensive benefits package to help you stay well, protect yourself and your family, and plan for a secure future. Benefits include generous time off; retirement plan with two-for-one matching contributions after the first year; many choices for comprehensive health insurance; life insurance; long-term disability coverage; and flexible spending accounts for healthcare and dependent care expenses. Learn more about U-M benefits. The University of Michigan conducts background checks on all job candidates upon acceptance of a contingent offer and may use a third-party administrator to conduct background checks. Background checks are performed in compliance with the Fair Credit Reporting Act. Institute for Social Research job openings are posted for a minimum of fourteen (14) calendar days. This opening may be removed from posting boards and filled any time after the minimum posting period has ended. The University of Michigan is an Equal Opportunity Employer. We are committed to providing an environment of mutual respect where equal employment opportunities are available to all applicants, including protected veterans and individuals with disabilities.