Senior Analytics Engineer, AI & DX Analytics
Block (Square) · Bay Area, CA, United States of America
About this role
## Block: Senior Analytics Engineer, AI & DX Analytics Block builds simple, powerful tools that help move toward an economy that’s truly open to all. Each brand unlocks different parts of the economy—Square, Cash App, Afterpay, TIDAL, Bitkey, and Proto—working together to build a financial system open to everyone. ### The Role The AI & DX Analytics team measures and improves Block’s developer experience and investment in AI. You’ll own parts of the analytics pipeline end to end: instrument new telemetry at the source, build production pipelines that turn it into governed data, and translate that data into executive-facing reporting and analysis that guides AI investment decisions. You’ll define new metrics, craft the visual narrative (charts, dashboards, and executive materials), and help ensure AI-first workflows are central to how the team builds and maintains pipelines and dashboards. ### You will **Instrumentation & Telemetry** - Instrument and extend raw telemetry about AI usage, code changes, CI/CD activity, and spend—building new data capture as signals evolve. - Partner with data engineers to land telemetry into governed tables with freshness monitoring, backfills, and alerting. - Define new metrics from ambiguous or evolving signals, validating and reconciling them until they earn stakeholder trust. **Dashboards & analysis** - Build and ship executive-facing dashboards and visualizations that turn governed metrics into decision-ready reporting. - Run the analysis behind new charts/metrics, anticipate executive questions, and bring recommendations (not just numbers) with defensible methodology. - Translate complex technical findings into a clear narrative—headline chart plus the one sentence that drives action. **Across both** - Use AI coding agents as a default part of writing, testing, and maintaining pipelines, dashboards, and analyses. - Partner across data engineering, applied AI, and data science to keep telemetry connected end to end (feeding session classifiers, not just dashboards). - Turn insights into action: flag where AI spend isn’t paying off or where developer friction is most costly, and drive tooling/process/investment changes. ### Qualifications - 8+ years in analytics engineering, data engineering, or business intelligence—owning production data pipelines and insights end to end. - Background in developer experience, engineering productivity, measuring AI effectiveness, or platform analytics. - Strong SQL and Python; hands-on experience building and operating pipelines against a cloud data warehouse (e.g., Snowflake). - Experience partnering with engineering teams to define and instrument new event/telemetry data. - Experience building dashboards or internal tools used by non-technical stakeholders to make decisions. - Comfortable owning a dashboard’s performance and data layer (profiling slow queries, improving caching/prequery layers, and shipping frontend changes—e.g., in React). - Comfort with git, CI/CD, and debugging production pipeline failures (retries, backfills). - Workflows built around AI coding agents as a primary tool for writing and maintaining code. - Strong written and verbal communication; able to present technical findings and methodology to senior stakeholders. - Track record of polished charts/materials for executive audiences (detail-oriented framing, labeling, and precision). - Demonstrated ability to lead cross-team collaboration. *Even better:* (additional qualifications were p
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