1. Gather, clean, and manage relevant data from various internal and external sources.
2. Develop and maintain efficient data pipelines and ETL processes to ensure data integrity and availability.
3. Implement data scraping methods to collect data from various sources relevant to governance and data tooling
4. Integrate external data with internal datasets to enhance analysis and provide comprehensive insights.
5. Validate data and process it to given formats
6. Transform and Embed data into A-usable formats
7. Document data analysis processes, methodologies, and findings.
8. Maintain clear and comprehensive records of data sources, tools, and techniques used.

• Language Skills: Fluent in English with strong verbal skills.
• Proficient in developing maintainable frameworks.
• Experience working with large-scale datasets in Python
• Proficient in working on remote Jupyter Notebook environments.
• Skilled in using Matplotlib and Pandas for data visualization and analysis.
• Knowledge of using Git in team environments.
• Statistical Knowledge: foundation in statistics.
• Technical Skills:
• Average proficiency in TS.
• Basic understanding of backend servers using Express.
• Work Ethic: Goal-oriented, self-sufficient problem solver with a strong work ethic.
• SQL Knowledge: Solid understanding of SQL.

Preferable

• Basic understanding of blockchain technology.
• Knowledge of artificial intelligence (AI) and some data engineering experience.
• Familiarity with Google Cloud (GCloud) and virtual environments.
• Experience with data scraping techniques.
• Understanding of various API types (e.g., GraphQL, REST).
• Doesn’t have to be web3 native as long as one is willing to learn