Okay, I've searched for Data Engineer roles in Riverwoods, IL that require a Bachelor's degree in Computer Science or related fields, are full-time, involve skills in AWS and Python, and offer a salary above $90,000. I have found 73 positions for you.

Sure. Here's the analysis:

Job Analysis:

This Data Engineer role at Discover is fundamentally centered on crafting, optimizing, and troubleshooting data integration pipelines essential for a large-scale, complex financial services environment. The candidate is expected to develop robust ETL solutions using a suite of contemporary technologies like Ab Initio, Python, Spark, and cloud platforms such as AWS, reflecting the company's need to manage voluminous, sensitive data efficiently and securely within its data warehouse ecosystem. The emphasis on agile methodologies and participation in cross-functional ceremonies signals a collaborative, iterative development culture where continuous improvement and teamwork are paramount. Success in this role demands not only technical expertise in data engineering fundamentals—including dimensional modeling and enterprise data architecture—but also an ability to influence peers and adapt solutions to evolving business requirements. Candidates must be adept at navigating high compliance and regulatory standards intrinsic to financial services, ensuring data accuracy and security. The expectation is that within the first 6 to 12 months, the engineer will contribute meaningfully to delivering reliable data integration workflows, supporting analytics and operational reporting, while demonstrating proactive problem-solving in a fast-paced, regulated environment.

Company Analysis:

Discover stands as a renowned player in U.S. financial services, combining the stability of an established brand with the dynamism required to innovate in digital banking and payments. Their positioning as a mature yet forward-looking institution means the environment balances risk-conscious practices with innovation, especially in data-driven decision-making and customer-centric solutions. Discover’s culture strongly reflects values of continuous improvement, collaboration, and customer focus, fostering a workplace where employees are encouraged to "play to win" while growing collectively. For a Data Engineer, this implies working in a culture that values not just technical delivery but agility, knowledge sharing, and responsiveness to evolving market demands. Being part of a team under the umbrella of a large corporate structure suggests transparency and access to leadership, but also necessitates navigating cross-departmental dependencies. Given Discover’s broad reach—from consumer credit to merchant services and international networks—this role feeds directly into strategic priorities around data integrity and innovation supporting scalable financial products. Overall, it is a fit for candidates seeking meaningful impact within a secure, mission-driven, yet agile company that values diversity and employee development.

Absolutely. Here are some mock interview questions that could come up:

• Behavioral: Tell me about a time when you had to troubleshoot a complex data integration failure. How did you identify the root cause and what steps did you take to resolve it?
• Behavioral: Describe an experience where you influenced team members to adopt a new data engineering practice or tool. What challenges did you face and how did you overcome them?
• Behavioral: Share an example of when you had to manage competing priorities in an agile development environment. How did you ensure commitments were met?
• Behavioral: Can you talk about a time you received constructive feedback about your work? How did you respond and implement changes?
• Technical: How do you approach designing an ETL pipeline to handle both batch and real-time data processing in a large enterprise data warehouse?
• Technical: Explain your experience with dimensional modeling and how you’ve applied source-to-target mappings in your previous projects.
• Technical: Describe how you have utilized cloud technologies like AWS in data engineering projects. What specific services or architectures did you leverage?
• Technical: How do you ensure data quality, security, and compliance during data integration in a regulated financial services environment?
• Situational: Imagine you discover that a critical data pipeline you built is producing intermittent errors affecting downstream analytics. How would you diagnose and fix this issue urgently?
• Situational: Suppose a product team requests a rapid data integration feature that conflicts with current architecture best practices. How would you balance speed with long-term maintainability?
• Situational: If you notice that your team is underperforming during agile ceremonies and missing sprint goals, what steps would you take to improve team dynamics and delivery?
• Company Fit: Why are you interested in working at Discover, particularly in the data engineering function within financial services?
• Company Fit: Discover emphasizes playing to win and succeeding together. How do your personal work values align with this culture?
• Company Fit: Given Discover’s commitment to compliance and customer-centricity, how would you approach ensuring your technical work reflects these priorities?
• Candidate Questions: Can you describe how data engineering teams collaborate with analytics and business units at Discover?
• Candidate Questions: What are the main data platform initiatives Discover is focusing on over the next 12 months?
• Candidate Questions: How does Discover support continuous learning and professional growth for data engineers?