Senior Data Engineer

Job summary

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.

Qualifications

• Job location –Rosemont, IL- Hybrid position with some telecommuting flexibility, but requirement to physically be in the Rosemont, IL office once a week.
• and prepare technical specifications and detailed level design documents.
• Serve as a resource to internal and third-party team members on escalated issues and analyze and design specifications for less experienced team members.
• Sees opportunities to deliver continuous process improvement, automating manual processes and optimizing data delivery.
• Design, development, test, and implementation of best-in-class Data Processing solutions for the organization, including Data Modeling, Data Loading, Data delivery, Data availability, Performance, and Security.
• Engage in all phases of the Data Enablement lifecycle and will be called upon to mentor less experienced team members as necessary.
• Design and build complete data pipelines moving and transforming data for ODS, Staging, Data Warehousing and Data Marts, MDM, including Middleware Integrations.
• Process semi structured and unstructured files using different traditional SQL and modern object-oriented scripting languages such as Python, etc.
• Build CICD pipelines for data pipelines using Azure DevOps.
• Requires a Bachelor’s degree in Computer Science, Computer Engineering, Information Systems, Engineering, Math, or a related field of study plus 7 years of experience in a related occupation.
• The position also requires:
• 5 years of experience in Data Engineering, designing, implementing data persistence, data processing, and data integration.

Responsibilities

• Design, develop, and continuously improve complex data systems.
• Build processes supporting data transformations, data structures, metadata, dependency, and workload management.
• Ensure data governance policies are followed by implementing and validating data lineage, quality checks, classification etc.
• Support/enhance/create Daily/Monthly ETL/ELT processes to ensure business continuity, ensuring all related data pipelines meet best-in-class standards, offering high performance.
• Create enterprise data sets for analytics and data scientist team members for advanced analytics.
• Create Conceptual/Logical/Physical Data Models for all data solutions.
• Seek opportunities to deliver continuous process improvement, automating manual processes and optimizing data delivery.
• Analyze the

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