Priya Shah Data Analyst
Chicago, IL • dataanalyst@gmail.com • +1 3122-2222
Profile Summary
- Data Analyst with 6 years of experience designing and operating business analytics platforms across marketplace operations, podcast growth, and consumer subscriptions, specializing in KPI design, A/B test readouts, and executive-facing data storytelling.
- Solid technical background across warehouses (Snowflake, BigQuery), BI tools (Tableau, Looker), languages (SQL, Python), statistics (R), and notebooks (Hex) with strong fundamentals in experiment design, causal reasoning, and dimensional modeling.
- Deep expertise in KPI ownership, experimentation rigor, self-service data culture, and executive-facing storytelling, leveraging methodologies such as weekly business reviews and A/B test readouts to drive actionable, well-documented, and trustworthy analytics.
- Engaged collaborator working cross-functionally with Product, Operations, and Finance teams in Agile environments, contributing to leadership reviews, launch postmortems, and metric-definition workshops with a pragmatic, ownership-first mindset.
- Emerging leader who shares technical excellence and fosters a culture of metric integrity and documentation discipline through PR reviews and runbooks, while leading analytics guild sessions and authoring widely adopted SQL-and-dashboard templates.
Technical Skills
- Data Warehouses:
- Snowflake, BigQuery, Redshift, Databricks
- BI & Visualization:
- Tableau, Looker, Mode, Power BI, Metabase
- Languages & Querying:
- SQL, Python (pandas, NumPy), R, Bash
- Statistics & Experimentation:
- A/B testing, CUPED, statsmodels, SciPy, causal inference
- Modeling & Semantic Layer:
- dbt, LookML, dimensional modeling, metric layer
- ETL & Pipelines:
- Airflow, Fivetran, Hightouch, dbt Cloud
- Notebooks & Discovery:
- Hex, Jupyter, Deepnote, Quarto
- Communication & Documentation:
- Executive briefings, board materials, RFCs, Atlan, Notion
Education
Northwestern
University
B.S. in
Statistics
Work Experience
DoorDash
Senior Data
Analyst
- Owned the business analytics workstream for the DoorDash Marketplace team supporting 35M+ active consumers, framing high-stakes questions across launch evaluation, funnel optimization, and market expansion for 8 product surfaces in collaboration with Product, Operations, and Finance leadership.
- Wrote production-grade SQL across Snowflake and dbt for 180+ recurring queries, refactoring slow joins and applying window functions, CTEs and modular subqueries, and incremental dbt materializations, reducing average query runtime from 48s to 6s and unblocking real-time stakeholder reporting.
- Built and maintained 22 Tableau and Looker dashboards for executive, product, and ops audiences, applying drill-down filters, derived calculations, and explainer tooltips, reaching 1,400+ weekly active users with self-service adoption climbing from 38% to 72%.
- Defined and documented 24 core business metrics including DAU/MAU, retention curves, and gross-order-value composition, governing them through a metric layer in dbt and a company-wide data dictionary, eliminating cross-team metric drift across 4 leadership reviews per quarter.
- Led 8 deep-dive analyses on top-of-funnel anomalies including a 22% drop in iOS new-user activation, isolating the cause to a routing-flag regression through cohort-by-cohort comparisons and shipping a fix that recovered $1.8M projected ARR.
- Supported 31 A/B tests for the Pricing and Subscription teams, designing experiment power and stratification, applying CUPED variance reduction, and producing causal vs correlational readouts that gated 9 experiment-driven launches without false-positive shipped wins.
- Authored 48 strategic narratives for executive reviews including board pre-reads, launch postmortems, and quarterly business retrospectives, translating cohort and funnel data into recommendations that shaped 3 multi-quarter strategic bets.
Spotify
Data
Analyst
- Profiled 120+ datasets across the Spotify Streaming Insights warehouse, identifying distribution skews, null-rate spikes, and schema drift, surfacing 15 upstream data-quality issues that blocked downstream model training.
- Owned the weekly and monthly reporting cadence for the Podcast Growth team, including listener cohort retention, show-level engagement, and creator-tier conversion, producing 120+ recurring reports that anchored the team's planning rituals over 2 years.
- Built the team's data documentation and self-service enablement program including metric definitions, column-level lineage in Atlan, and weekly stakeholder office hours, reducing analyst-on-call requests by 62% and lifting stakeholder NPS from 34 to 78.
- Worked closely with Product, Marketing, and Operations teams across 4 product surfaces to negotiate metric definitions, launch quality bars, and dashboard ownership models, authoring 6 analytics RFCs that shaped the org's data culture and onboarding 8 new analysts.