Senior Business Intelligence Analyst

<p>Block is one company built from many blocks, all united by the same purpose of economic empowerment. The blocks that form our foundational teams — People, Finance, Counsel, Hardware, Information Security, Platform Infrastructure Engineering, and more — provide support and guidance at the corporate level. They work across business groups and around the globe, spanning time zones and disciplines to develop inclusive People policies, forecast finances, give legal counsel, safeguard systems, nurture new initiatives, and more. Every challenge creates possibilities, and we need different perspectives to see them all. Bring yours to Block.</p> <h3>The Role</h3> <p>Do you love transforming data into meaningful insights that drive real impact? Join Block's Engineering Operations (EngOps) team, where you'll shape how our engineering organization works and makes decisions. Your analysis will inform strategy, enhance operational efficiency, and help thousands of engineers deliver with greater speed and quality.</p> <p>EngOps provides data-driven insights that enable leaders and teams to work more effectively. We partner across engineering, product, and cross-functional groups to guide strategic decisions, optimize resources, and enable continuous improvement.</p> <p>As part of this distributed team, you'll report to the Strategic Insights Lead and turn complex quantitative and qualitative data into actionable recommendations. You'll drive research and analysis, surface cross-domain insights, collaborate with data engineering, and build automated reporting that tracks progress and strengthens engineering effectiveness.</p> <h3>You Will</h3> <ul> <li>Drive quantitative and qualitative research on operational performance of the engineering organization</li> <li>Conduct cross-functional data discovery, combining quantitative analysis with qualitative insights from partner interviews</li> <li>Develop and test hypotheses to improve engineering effectiveness toward Block's strategic business goals</li> <li>Apply advanced statistical methods to interpret complex data sets and surface latent relationships in the data</li> <li>Combine AI-enabled and traditional research methods to gather, transform, and analyze both quantitative and qualitative data</li> <li>Curiously and continuously explore new opportunities for applied AI in research of organizational effectiveness</li> <li>Collaborate with Data Engineering, SREs, Developer Experience, and People Analytics to ensure data matches reality</li> <li>Prepare detailed summaries of your analysis with clear recommendations</li> <li>Automate reporting to track results of key initiatives that emerge from your recommendations</li> <li>Integrate data into AI-enabled workflows to enable data-informed decisions at scale</li> <li>Develop and maintain comprehensive view of technical health metrics</li> <li>Apply AI to automate routine analysis and reporting; reserve hands-on work for strategic and high-impact exercises</li> </ul> <h3>You Have</h3> <ul> <li>5+ years of experience solving complex data problems, preferably with a focus on operational metrics and organizational effectiveness</li> <li>Strong skills in research, statistical analysis, and querying complex data (particularly SQL)</li> <li>Familiar with DevOps and a strong understanding of software delivery metrics (e.g. DORA, incident mgmt, SLO frameworks)</li> <li>Capable of working independently, prioritizing tasks, and delivering results with minimal supervision</li> <li>Proven track record of driving high-impact data projects with cross-functional teams</li> <li>Experience with version control systems and collaborative development practices (e.g. Git)</li> <li>Technical skills to build and maintain ETLs and other data pipelines</li> <li>Experience designing, building, and maintaining scalable data models and schemas</li> <li>Qualitative research skills (e.g. focus groups, interviews)</li> <li>A knack for storytelling and visualizing answers to c ... (truncated, view full listing at source)