Okay, I've searched for Senior Data Engineer positions in Draper, UT, requiring 4+ years of experience with Hadoop and Spark, full-time roles in the Information Technology industry. I have found 27 positions for you.

Sure. Here's the analysis:

Job Analysis:

The AVP, Senior Data Engineer role at Synchrony is fundamentally about architecting and advancing a cutting-edge Big Data environment that empowers consumer-focused, real-time analytics at scale. Beyond the technical build—which involves Hadoop, Spark, Kafka, Redshift, and related technologies—the role requires translating complex technical challenges into actionable deliverables while driving modernization from legacy systems to a more agile, enterprise-level data ecosystem. This is not just about handling data pipelines but about enabling rapid, low-latency insights that directly influence business outcomes such as credit decisioning and consumer engagement. Success in this role means delivering robust, scalable data solutions that anticipate evolving business needs and collaborating effectively across product owners, architects, and developers in an Agile environment. The position demands a blend of deep technical expertise in big data tools and platforms, mastery of CI/CD practices for ongoing delivery, and strong communication skills for stakeholder alignment and leadership influence. Managing ambiguity, prioritizing among shifting demands, and advocating enterprise-wide standards all indicate a highly strategic problem-solving environment with substantial autonomy and expectation for proactive innovation.

Company Analysis:

Synchrony operates as a leading consumer financial services company with a unique market position focused on enabling accessible financing options for millions, underpinning its role in everyday consumer and business ecosystems. This places the company at the intersection of finance and technology, where data agility and security are paramount. Synchrony’s culture emphasizes flexibility, inclusion, and participant empowerment, revealing an environment that values not only technical expertise but also diverse perspectives and holistic collaboration. The strategic vision to help consumers make smarter credit decisions through innovative tech-based analytics means this data engineering role will be highly visible and influential, especially given the data-driven orientation of financial services today. Moreover, the company's commitment to flexible work and inclusion signals a progressive and supportive workplace, beneficial for sustained innovation. Organizationally, this position is a senior individual contributor or technical lead who bridges architecture, engineering, and product, placing the holder in a critical position to align data strategy with business growth and transformation initiatives. Overall, this is a role that not only supports Synchrony’s ambition to modernize its infrastructure but also contributes to the broader mission of financial empowerment and economic impact.

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

• Behavioral: Tell me about a time when you had to manage competing priorities in a fast-paced, evolving technical environment. How did you ensure successful delivery?
• Behavioral: Describe an instance where you influenced cross-functional teams to adopt a new technology or process standard. What challenges did you face and how did you overcome them?
• Behavioral: Can you share an example of how you communicated a complex technical concept to a non-technical stakeholder? What approach did you take to ensure understanding?
• Behavioral: Give an example of a difficult problem you solved using rigorous analytical methods in a data engineering context. What was your process?
• Technical: Explain your approach to designing and implementing a big data lake environment using Hadoop, Spark, and Kafka. What architectural considerations do you prioritize?
• Technical: How do you ensure performance tuning and optimization in large-scale data pipeline systems involving both batch and real-time ingestion?
• Technical: Describe your experience with CI/CD pipelines in data engineering projects. How do you apply Git, Jenkins or similar tools to maintain delivery velocity and quality?
• Technical: What is your familiarity with data cleansing and transformation at scale? Can you walk us through a project where you handled semi-structured or unstructured data?
• Situational: Imagine you discover that a critical real-time data feed is intermittent and causing downstream analytics delays. How would you diagnose and resolve this issue?
• Situational: Suppose there is a conflict between the platform administrators and the product owners regarding delivery timelines and technical feasibility. How would you navigate this situation?
• Situational: You're asked to modernize a legacy data ingestion system that lacks scalability and documentation. What steps would you take to transition this system while minimizing business disruption?
• Company Fit: Why are you interested in working for Synchrony, particularly in a senior data engineering role focused on consumer financial services?
• Company Fit: How do your personal values and work style align with Synchrony's commitment to inclusivity, flexibility, and innovation?
• Company Fit: Considering Synchrony's diverse ecosystem of small- and mid-sized business partners, how would you leverage data engineering to enhance their experience?
• Questions for Interviewer: Can you describe the typical cross-team collaboration process for large data initiatives here at Synchrony?
• Questions for Interviewer: How does Synchrony measure success for this Senior Data Engineer role in the first year?
• Questions for Interviewer: What are some of the biggest technical challenges the data engineering team is currently facing in modernizing legacy systems?