Senior Tech Data Analyst

Wintrust provides community and commercial banking, specialty finance and wealth management services through its 16 bank charters and nine non-bank businesses. Wintrust delivers the sophisticated solutions of a large bank while staying true to the relationship-focused, personalized service of our community banking roots. We serve clients in all 50 states with more than 200 branch banking locations in Illinois, southwestern Florida, northwestern Indiana, west Michigan and southern Wisconsin and commercial banking offices in Chicago, Denver, Milwaukee, Grand Rapids, Mich.,

and in key branch banking locations throughout Illinois. Our people are the heart of our business and we are proud to rank consistently as a top place to work. Wintrust is a $66 billion financial institution based in Rosemont, Illinois, and listed on the NASDAQ Global Select Market under the symbol “WTFC.”

An award-winning culture! We are rated a Top Workplace by the Chicago Tribune (past 10 years) and Employee Recommended award by the Globe & Mail (past 6 years) Competitive pay and discretionary or incentive bonus eligible Comprehensive benefit package including medical, dental, vision, life, a 401k plan with a generous company match and tuition reimbursement to name a few Family-friendly work hours With 175+ community bank locations, we offer opportunities to grow and develop in your career Promote from within culture

We have a culture that encourages an entrepreneurial spirit We offer multiple opportunities for development and upward mobility

The Senior Technical Data Analyst plays a pivotal role in enabling the bank to leverage both structured and unstructured data as trusted, enterprise information assets. Operating within the Data Management team, this role is responsible for transforming complex data – ranging from core banking systems to documents, communication, and external data sources – into actionable intelligence. This role bridges business, analytics, and technology to deliver insights, and support governance and growth initiatives.

Analyze large, complex structured data sets (example – transactions, customer, risk, finance data) alongside unstructured data (example – documents, emails, transcripts, PDF etc). Apply analytical techniques to extract insights, detect patterns, and identify risks or opportunities. Support a wide variety of enterprise data use cases across AML/KYC, fraud, customer experience, regulatory reporting, and operational efficiency.

Partner with data engineering and product teams to enable ingestion, classification, and analysis of unstructured data. Support text analytics, document parsing, metadata extraction to make unstructured data usable and governed. Adopt defined standards for tagging, cataloging, and governing unstructured data assets.

Work closely with business, risk, compliance, and operations teams to translate business needs into data use cases. Break down ambiguous problems into structured approaches. Ensure alignment between business objectives, regulatory requirements and data solutions. Ensure transparency and defensibility of insights derived from structured and unstructured sources.

Contribute to building reusable, governed, and high-quality datasets aligned to business outcomes. Ensure data assets are documented, discoverable, and fit for purpose. Enable cross-domain reuse of data to reduce duplication and improve consistency.

Adopt enterprise data governance defined frameworks across both structured and unstructured data domains. Identify data…