Sr. Data Engineer (Blockchain)

SAMPLE #1 Resume

Digital Assets Fund, Blockchain Data

• Reduced annual data spend by $190k by scrapping websites and directly connecting to blockchains using Go RPCs and nodes hosted on cloud (AWS, Google BigQuery) then parsed data using Python and visualized on Streamlit.
• Automated dashboards and reports, which ran through manual intervention before, using AWS lambda saving ~90 hours of monthly labor.
• Built a python library and API that abstracts complex blockchain queries for smart contract platforms (including Ethereum, Solana, Cardano, Cosmos etc.)

SAMPLE #2 Resume

Data Analytics Engineer

• Deep Liquidity Analysis - Implemented real-time crypto exchange order book streaming system using Python, Airflow, Snowflake, Kafka. Created data pipeline and maintained the ETL pipeline for data dashboard.
• Data Platform Management - Built and maintained a centralized data platform on Azure SQL, Python, Airflow and Snowflake. Developed and maintained over 100+ ETL pipelines, powering >10 PetaByte data sources.
• Blockchain data analytics - Created data engineering workflow using Python, Snowflake, Azure, Zendesk API, and machine learning classification to predict wallet downtime, resulting in improved prioritization of customer support tickets, increased agent productivity and reduced operational costs for Wallet Operations team. Presented KPI's using a Streamlit dashboard.
• Client OPS for Order Spoofing - Assisted in the deployment of machine learning model for trading related fraud detection by implementing a scalable machine solution using technologies such as Spark, Docker and Kubernetes.
• Experimentation Platform : Built the data pipeline for experimentation platform using Python, Snowflake, Airflow and Streamlit to automate A/B testing for marketing team.
• Crypto Market research – Conducted weekly research and analysis on latest crypto protocols( AMM, consensus algorithms, Tokenomics etc.) to help wallet, Finance team.

• They are looking for advanced skills in Python. R experience could be swapped out, but they would have to adapt very quickly.
• They are looking for a true Data Engineer, not a Data Scientist.
• Web3 experience - They do prefer Web3 experience. Since it's not common then they will talk with someone who meets the other criterias first (mentioned above) + blockchain interest.
• Hands on exp AWS cloud – google could work.
• Pandas exp desired
• Any crypto/blockchain companies experience works

• Interview process: 30 mins with Johnathan
• 1 hour video tech - review resume/experience, skills, topics of project
• Presentation to team
• 30 mins with CTO then CEO - general convo to get to offer

• You'll work with a cross-functional team of research scientists and engineers to contribute to our software and data platforms.
• Drive the design and implementation of data models, ETL pipelines, and data processing logic while working closely with the other teams in order to translate operational data with microservices into business value.
• Collaborate in proof of concepts (POCs) from research concepts and then lead building those in a production environment.
• Work on complex problems ranging from mathematical proofs to big data processes to fueling research with blockchain, financial, and gaming metrics.
• We are looking for someone with a curiosity for data and the ability to iterate quickly in an ambiguous environment.
• Preferred experience with finance, gaming/crypto gaming, blockchain, or crypto protocols.
• Bonus Domain expertise in one or more areas: finance, gaming, DeFi, cryptocurrency, blockchain, and smart contracts.

• Advanced skills with python (or similar language) for data collection, analysis, and communication including familiarity with pandas package, object-oriented programming, and built-in functions.
• Experience in Web3 including smart contract development, blockchain data, and DeFi protocols such as Uniswap.
• Hands-on experience in AWS Cloud services including building and implementing server and serverless data engineering, data science, and analytics infrastructure. Bonus for experience integrating services such as Airflow.
• Experience communicating and delivering results with data scientists, machine learning, and modeling valuable to implementing use cases.
• Understanding of Test-Driven Development.
• Good knowledge of ETL, data warehousing, and pipelines design.
• Preferred 5+ years of experience in a data focused role including ETL, querying data with SQL, data modeling, data collection, data analysis, and data science.
• Curiosity, empathy, and an interest in working with a team with a high degree of collaboration.
• An ability to adapt and work under large amounts of uncertainty and ambiguity.