Data Analyst

Experience 9+ 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 — Visualization Deep, 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 Skills Strong 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 Working Native 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.