Data Analyst

Experience9+ years of combined experience in Data Analytics, Business Intelligence, or Analytics Engineering roles.At least 3+ years at Senior level or above in an analytics-adjacent role at a high-scale tech, ads-tech, marketplace, or fintech company.Prior experience as the most senior analytics IC on an embedded team — or a strong case for why they're ready to step into that role now.Track record of leading end-to-end analytics initiatives — from ambiguous business question through data model, pipeline, dashboard, and rollout.Prior experience partnering directly with US-based Data Science, Product, and Engineering leaders as a full contributor.Technical Skills — SQL & Data Engineering (Advanced)Expert-level SQL — deep proficiency with window functions, CTEs, complex joins, query optimization, incremental patterns, skew mitigation, and cost tuning on billion+ row tables.Deep hands-on with at least two of: Presto, Trino, Hive, Spark SQL, Snowflake, BigQuery, Redshift. Can reason about query plans and physical layout, not just syntax.Advanced Airflow — has architected and operated large DAG ecosystems (50+ production DAGs), including cross-DAG dependencies, backfills at scale, and SLA management. Equivalent orchestrators (Dagster, Prefect) also acceptable if depth is comparable.Data architecture & modeling depth — Kimball, star schema, dimensional modeling, OLAP cubes, wide fact tables, slowly-changing dimensions, semantic layer design. Can defend design tradeoffs in a design review.ETL / ELT architecture — incremental loads, backfills, idempotency, data quality frameworks, lineage.Python for data work — pandas, PySpark, scripting, and light tooling development.dbt or equivalent transformation framework experience strongly preferred.Experience contributing to or reviewing design docs and RFCs for data platforms and pipelines.Technical Skills — VisualizationDeep, hands-on production experience building executive-grade dashboards in Tableau and/or Apache Superset (Looker, Power BI, Mode also acceptable).Strong opinions on dashboard design — headline vs. drilldown metrics, layout, filters, performance, self-serve UX.Experience driving metric governance and self-serve BI at an org level.Analytics & Business SkillsStrong grasp of KPI definition, metric design, funnel analysis, cohort analysis, and A/B testing methodology.Deep exposure to digital advertising / monetization metrics — impressions, clicks, CTR, CPM, CPC, CVR, ROAS, revenue attribution, incrementality — is strongly preferred.Prior experience at ads-tech, digital media, or major consumer/marketplace tech companies (Meta, Google, Amazon, Uber, DoorDash, Snap, TikTok, LinkedIn, Airbnb, Instacart, Pinterest peers, etc.) is a strong plus.Comfort reading experiment results and challenging methodology when needed.Leadership, Communication & Ways of WorkingNative or near-native English (spoken and written) — this is a hard requirement.Track record of leading initiatives end-to-end with minimal direction — scoping, aligning stakeholders, executing, and communicating results.Comfortable pushing back on unclear or misdirected requirements and proposing better approaches.Prolific writer of design docs, RFCs, requirement docs, and postmortems.Experience mentoring or coaching less-senior analysts and analytics engineers — even if not a formal manager.Executive presence — can present analytics work to Director/VP-level stakeholders and defend recommendations.Operates with the ownership mindset of a permanent employee, even in a contract role.