Salary
💰 $85,000 - $130,000 per year
Tech Stack
AirflowAmazon RedshiftAWSAzureBigQueryCloudETLGoogle Cloud PlatformNumpyPandasPythonScikit-LearnSQLTableauVaultWeb3
About the role
- Build and maintain data pipelines that power both ad-hoc analyses and production dashboards
- Develop statistical models and data science solutions while also implementing the infrastructure to deploy them
- Create self-serve analytics tools and datasets that empower stakeholders across the organization
- Design experiments and perform statistical analyses to measure product and marketing initiatives
- Build data models in our warehouse that balance analytical flexibility with performance
- Partner directly with product, marketing, and leadership teams to identify opportunities and measure impact
- Own the full lifecycle of data products - from initial exploration to production deployment
Requirements
- Strong experience with modern data stack tools (e.g., dbt, Airflow/Dagster, Snowflake, BigQuery, Redshift, or similar)
- Proven ability to design and manage ETL pipelines and database architectures
- Advanced SQL skills and high proficiency in Python for both data analysis and engineering
- Understanding of data modeling principles (Kimball, Data Vault, or similar)
- Experience with cloud data platforms (AWS, GCP, or Azure)
- Strong statistical analysis skills with hands-on experience using Python data science stack (pandas, NumPy, scikit-learn)
- Experience with A/B testing, causal inference, and experimental design
- Ability to communicate complex findings to non-technical stakeholders
- Track record of using data to influence business strategy
- Hands-on experience with blockchain data extraction, transformation, and analysis
- Understanding of EVM concepts (transactions, events, smart contracts) and/or non-EVM ecosystems
- Ability to work with on-chain data to derive actionable insights