Data Architect

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Working at the University of Michigan Institute for Social Research (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 focuses 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 highly experienced, hands‑on, and forward‑thinking Data Architect to own the architectural vision and roadmap for our data warehousing, reporting, and data delivery automation. In this role, you will define and implement data architecture standards and frameworks, enterprise‑scale data models, and guide engineering teams in implementing scalable, high‑performance data pipelines and platforms.

You will serve as the technical authority on data architecture decisions, ensuring our systems adhere to sound data governance principles, maintain data integrity, and meet the evolving needs of the business. You will collaborate cross‑functionally to bridge the gap between raw data and actionable insights, driving alignment between data strategy and organizational goals. This is a hybrid position located in Ann Arbor, Michigan.

• Design, build, and optimize enterprise data architectures across cloud and on‑premises platforms, including data warehouses, operational data stores, pipelines, schemas, APIs, and integration patterns.
• Own the architecture and evolution of the SQL Server Operational Data Store, consolidating survey project data from 12+ source systems for near‑real‑time reporting and field operations, including infrastructure migration, version road mapping, and extension into a historical data warehouse.
• Identify authoritative sources of truth across heterogeneous operational systems and design integrated relational models that support reporting and downstream applications while preserving clarity around system ownership and data authority.
• Lead hands‑on development of data solutions, including ETL/ELT workflows, Python‑based ingestion pipelines, REST/GraphQL integrations, file‑based imports, operational database extracts, validation logic, business rules, and performance‑tuned SQL.
• Maintain and extend metadata‑driven data services, including curated views, stored procedures, data dictionaries, attribute schemas, dynamic query definitions, UI configuration, and API‑layer structures that enable downstream tools without code releases.
• Own and evolve SQLXtend, an internal Python data integration framework, including ongoing development, documentation, adoption, and use across team pipelines.
• Define and enforce data governance practices, including data standards, metadata management, lineage, data quality controls, security, privacy, compliance, and reliable use of enterprise data assets.
• Lead database administration and reliability efforts in partnership with a DBA, including monitoring, backups, replication, performance tuning, indexing, query optimization, capacity planning, security, high availability, and SQL Server upgrades.
• Supervise and mentor technical staff, including DBAs, developers, SQL coders, report writers, modelers, analysts, and data engineers by setting technical direction, managing workloads, reviewing deliverables, conducting…