Data Lead
Canvas
AirflowBigQueryGoPythonSQL
Salary
💰 $100,000 - $200,000 per year
Job Level
Senior
Tech Stack
AirflowBigQueryETLJavaScriptNode.jsOraclePythonReactSoliditySQLTypeScriptWeb3
About the role
- Drive the analytics agenda by applying a product mindset to identify and prioritize the most impactful product and business questions, independently performing deep, hands-on analyses, and delivering dashboards and reports that shape strategic decisions.
- Collaborate closely with data engineering to onboard and model new data sources. Write SQL/Python (or similar) scripts to source, extract, clean and optimize analytics-ready data for downstream uses–balancing rigor with speed.
- Act as the analytics partner for Product, Engineering, and company leadership, surfacing trends, anomalies, and opportunities early, and translating data into clear, actionable recommendations.
- Ensure the data leveraged for analytics is accurate, well-structured, and aligned with business priorities, focusing effort where it drives the most impact.
- Leverage deep understanding of crypto, DeFi, interoperability to contextualize data, anticipate emerging trends, and convert historical insights into forward-looking recommendations.
Requirements
- 5+ years experience in advanced data/analyst roles in related industries, with a preference for at least 2 years leading the function/team.
- Mastery of SQL and Python; strong experience in data modeling, ETL or data pipeline scripting, and business-intelligence/dashboard tools.
- Demonstrated ability to craft the right analytical questions, think critically, balance speed versus depth, and deliver insights that drive measurable business outcomes.
- Outstanding critical thinking skills; low ego, high curiosity and comfort in being wrong.
- Excellent organizational skills, attention to detail, and time management.
- Excellent collaboration and communication skills.
- Comfortable with and eager to adapt to the evolving role of AI in modern work.
- Deep industry insight with a solid understanding of crypto markets, DeFi, interoperability challenges, and the ability to weave these into analytics.
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