Okay, I've searched for Data Engineer Analyst roles in Greensboro, NC that are full-time, requiring 1-3 years of experience, with skills in Python and SQL, and including tuition assistance. I have found 142 positions matching your criteria.

Sure. Here's the analysis:

Job Analysis:

The Data Engineer Analyst role at Lincoln Financial within the Customer360 team is fundamentally designed to enable the enterprise's data-driven decision-making through managing and enhancing a complex data lake and mastering platform. This role goes beyond typical data engineering to include active collaboration with data scientists, business stakeholders, and architects to support predictive analytics, machine learning, and AI initiatives. The incumbent’s responsibilities span data pipeline development, cleansing, quality improvement, and modeling to transform fragmented raw data into reliable, actionable insights that align with strategic corporate goals. The requirement for familiarity with AWS cloud services, CI/CD pipelines, Dataiku, and visualization tools such as Tableau or PowerBI reflects a need to operate within a modern, scalable, automated environment supporting cross-enterprise data use. The candidate must be comfortable navigating complexity and ambiguity—organizing multi-source data, understanding interdependencies, and advising management on analytic best practices—necessary for effective business outcomes in a regulated and risk-aware financial context. Success in this role is demonstrated by delivering high-quality, scalable data infrastructure enhancements that reduce manual workloads, improve data integrity, and enable predictive analytics projects to flourish, while fostering strong cross-functional partnerships.

Company Analysis:

Lincoln Financial is a venerable and trusted player in the financial services industry, with a 120-year legacy focused on empowering customers’ financial security through insurance, annuities, and retirement solutions. Positioned as a market leader with a steady, innovation-conscious growth trajectory, the company values integrity, inclusion, and career development, emphasizing a supportive, mission-oriented culture that encourages employees to thrive and contribute meaningful expertise. For a Data Engineer Analyst, this environment offers the opportunity to work on impactful, large-scale enterprise data solutions that help millions of clients reach financial goals, while benefiting from structured career paths and leadership development programs. The culture encourages collaboration across teams and is likely hybrid yet flexible, reflecting a balance of tradition and modern workplace needs. This role sits strategically within the Customer360 platform—a key technology pillar—offering visibility and influence in shaping how data fuels advanced analytics and business transformation. Hiring for this role suggests a strategic push to enhance Lincoln’s data capabilities, support AI initiatives, and scale data infrastructure for future growth, making it an excellent fit for professionals ready to contribute in a mature, values-driven environment that actively invests in technology and people.

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

• Tell me about a time when you had to collaborate with multiple stakeholders, such as data scientists and business users, to develop a data solution. How did you ensure their requirements were met?
• Describe a complex data pipeline you designed or improved. What were the key challenges, and how did you address data quality and reliability?
• Can you share an experience where you identified and implemented a process improvement that reduced workload or improved data accuracy? What impact did it have?
• How have you handled ambiguity or incomplete data in prior projects? What steps did you take to manage uncertainty and deliver usable insights?
• Explain your experience with AWS cloud services such as EKS, EC2, or S3 in the context of data engineering projects. How did you leverage these tools to support your work?
• What is your approach to building and maintaining ETL pipelines using CI/CD tools like GitLab? How do you ensure continuous integration and deployment are effective in your workflow?
• Describe how you would prepare data from diverse sources for prescriptive and predictive modeling in a financial services context.
• Have you worked with platforms like Dataiku or similar modeling/automation platforms? How do these tools enhance your data engineering practices?
• Imagine you detect a recurring issue with data inconsistencies impacting a business intelligence report. How would you diagnose and resolve the problem while communicating with stakeholders?
• How would you prioritize multiple enhancement requests from different teams using the Customer360 platform? What factors would guide your decision-making?
• Why are you interested in working at Lincoln Financial, particularly within the Customer360 data platform team?
• How do you see Lincoln Financial’s commitment to diversity and inclusion influencing your work environment and collaboration on data-driven projects?
• Given Lincoln Financial’s mission to empower customers’ financial futures, how would you align your technical contributions to serve this broader goal?
• What challenges do you anticipate in transitioning to a hybrid work model here, and how would you manage cross-team coordination with some colleagues remote and others onsite?
• Can you share a few questions you have about the data team’s roadmap or Lincoln’s use of advanced analytics and AI that would help you understand your potential impact?