Okay, I've searched for Senior Data Analyst roles in Pittsburgh, PA within the Banking and Finance industry, requiring 10+ years of experience, with hybrid work mode, and skills in SQL, Spark, and Python. I have found 34 positions matching your criteria.

Sure. Here's the analysis:

Job Analysis:

This Senior Data Analyst role is fundamentally about bridging deep technical expertise with strong business understanding within the retail banking domain. The candidate is expected to not only analyze complex datasets but also actively participate in the end-to-end lifecycle of data solutions—from gathering and refining business requirements, through coding and prototyping, to full production implementation. This requires fluency in advanced data platforms such as Hadoop, Teradata, and Oracle and programming languages including SQL, Spark, and Python, illustrating the need for hands-on, production-level coding skills rather than just data querying or analysis. The role goes beyond mere data manipulation to include designing nimble, scalable data solutions and embedding critical business rules, showing a strategic impact on how data supports retail lending products like loans and deposits. Crucial soft skills include cross-functional collaboration with both technical teams and non-technical business partners in an agile environment, requiring clear communication, documentation, and problem solving to navigate iterative projects and continuous delivery. The successful candidate must excel at managing competing priorities and ambiguity inherent in large-scale data initiatives, providing timely and insightful data-driven decisions. Performance in this role is likely measured by accuracy and impact of data solutions, adherence to production timelines, and the ability to support multiple data domains effectively within retail banking. The role demands over a decade of relevant experience, signaling a senior-level responsibility with autonomy in decision-making around architecture and solution design, as well as mentorship possibilities given the complexity and scope of work.

Company Analysis:

System One operates as a strategic workforce solutions provider with a strong presence in IT and data-driven staffing, aiming to deliver high-quality talent to industries like banking and finance. The partnership with Lensa, a technology-driven job platform leveraging AI and machine learning, reflects an innovative commitment to transforming traditional hiring and career development paradigms. This is a hybrid environment blending technology and human factors, emphasizing agility and precision in talent placement and solution delivery. For a Senior Data Analyst, this means working within a dynamic, fast-paced, tech-enabled culture that values deep domain expertise in retail finance paired with cutting-edge data engineering and analytics capabilities. The company culture likely prioritizes collaboration across business and technology teams and a mission-oriented mindset focused on problem-solving to drive client success. This role’s hybrid work mode and multi-location flexibility suggest a balance between independent, focused work and necessary teamwork. Being a contract-to-hire position further implies a mutual evaluation period, where demonstrating adaptability, technical excellence, and cultural fit will be critical. Organizationally, the role sits as a key contributor embedded within cross-functional agile teams, offering potential visibility to leadership through impactful delivery and partnership with business domains. Ultimately, this hire serves a strategic function in enabling the company and its clients to leverage deep data insights for competitive advantage in the retail banking sector, aligning perfectly with System One’s goal to not just staff talent but to foster transformative digital outcomes.

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

• Behavioral: Tell me about a time when you had to translate complex business requirements into a technical data solution. How did you ensure clarity and alignment between technical teams and business partners?
• Behavioral: Describe an example of when you faced conflicting priorities or ambiguity in a data project. How did you manage the situation and what was the outcome?
• Behavioral: Share an experience where you had to resolve a significant data-related issue in a production environment. What steps did you take to diagnose and fix the problem?
• Behavioral: How have you collaborated with Agile teams in your previous roles? What strategies did you use to stay organized and communicate effectively in such settings?
• Technical: Walk me through your experience writing code in SQL, Spark, and Python for big data platforms like Hadoop or Teradata. How do you optimize data processing for performance and scalability?
• Technical: How would you approach designing and implementing a new data solution to support retail lending data domains? What factors would you consider from a technical and business perspective?
• Technical: Can you explain your experience with automation tools like Oozie or Slurm? How have they improved your workflow in data pipeline management?
• Technical: Discuss how you utilize data visualization tools such as Tableau or Power BI to support business analytics. How do you ensure your visualizations drive informed decision-making?
• Situational: Imagine during a sprint you receive a last-minute urgent ad hoc data request that conflicts with your current deliverables. How would you handle this situation?
• Situational: Suppose you identify inconsistencies in a critical dataset for retail loan analysis just before production deployment. What steps would you take to address this?
• Situational: If a business partner challenges the validity of your data analysis or solution, how do you respond to maintain trust and clarity?
• Company Fit: What interests you about working with System One and Lensa, especially in the context of retail banking and career technology?
• Company Fit: How do your personal values and professional goals align with System One’s mission to provide efficient, quality workforce solutions?
• Company Fit: Given the contract-to-hire nature of this role, how do you plan to demonstrate your value and adaptability during the initial period?
• Questions for Interviewer: How does the data analytics team at System One collaborate with Lensa and other technology partners to drive innovation in retail finance?
• Questions for Interviewer: What are the biggest challenges currently faced by the data domain teams supporting retail lending, and how could this role help address them?
• Questions for Interviewer: How does System One support ongoing professional development and career growth for senior analysts within hybrid work arrangements?