Okay, I've searched for Lead Data Engineer roles in Chicago focusing on GCP technologies, requiring 5+ years of experience, offering hybrid work arrangements, and with competitive salary options. I have found 27 positions matching your criteria.

Sure. Here's the analysis:

Job Analysis:

The Lead Data Engineer role at 84.51° is fundamentally about driving innovation and excellence in data engineering practices while leveraging large volumes of retail data to improve customer-centric strategies. The primary responsibilities include designing and maintaining scalable data pipelines, implementing advanced feature engineering techniques, and mentoring team members. This role emphasizes the importance of not only technical expertise in cloud platforms (GCP and Azure) and tools like Kafka, but also the ability to lead cross-functional collaborations and ensure clear communication across diverse teams. The candidate will face challenges such as managing complex data workflows and optimizing processes for performance and cost efficiency. Success in this role is reflected by robust, efficient, and secure data solutions that meet organizational standards, alongside improved team capabilities resulting from effective mentorship.

Company Analysis:

84.51° positions itself as a leader in retail data science, utilizing vast insights derived from consumer interactions with The Kroger Co. and other clients in the retail landscape. As a data-driven company, innovation and a deep understanding of consumer behavior are at the core of its operations. The culture appears to be heavily focused on teamwork, collaboration, and a commitment to leveraging data for impactful marketing solutions, implying a fast-paced and evolving work environment. This role sits within an agile framework, likely working closely with various teams to refine and enhance data processes. The strategic alignment of this position emphasizes growth and modernization of data assets to better serve customers, positioning the Lead Data Engineer as a key player in maintaining and advancing the company's competitive edge in the market.

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

• Describe a time when you led a cross-functional team to solve a complex data engineering challenge. What was the outcome?
• Can you give an example of a project where you had to design a data pipeline? What technologies did you use, and what challenges did you face?
• Tell me about a time you had to mentor a less experienced team member in data principles or practices. How did you approach it?
• How would you implement automated testing for a newly developed data pipeline, and what factors would you consider for data quality?
• What strategies would you employ to optimize data workflows in a system handling extremely large datasets?
• How do you approach feature engineering for machine learning workflows? Can you discuss your experience with Vertex AI or BigQuery ML?
• Imagine you're facing scalability issues with a data pipeline. What steps would you take to identify and address the problem?
• Suppose you have to present a cost/benefit analysis for a new data solution to leadership. What key aspects would you include in your presentation?
• What interests you about working at 84.51°, and how do you see your skills aligning with the company's mission?
• How do you stay informed about the latest trends in data engineering and data science, and how would you apply them in this role?
• Do you have any experience with Structured Streaming technologies like Spark or Kafka? How have you used them in past projects?
• What questions do you have about the team or the specific projects you would be working on at 84.51°?
• Can you describe your experience with CI/CD pipelines? How have they improved your data development processes?