Blockchain Data Analyst & Researcher

Lukka is a company focused on solving complex data and technology challenges in the digital assets industry. It operates a Poland-based team collaborating with US and global stakeholders to address regulations and educate customers about crypto tax implications and accountability.

Experience:

• 3+ years hands-on in Data Science, Data Engineering, or hybrid roles.
• Blockchain or crypto analytics background with familiarity in on-chain data structures and transaction semantics.

Streaming & Lakehouse:

• Experience with Apache Flink or Spark Streaming for real-time data pipelines.
• Familiarity with Apache Iceberg or Apache Hudi for large-scale Data Lakehouses.

AWS Data Platform:

• Experience with S3 for data lake storage; RDS for relational workloads.
• Proficiency with Spark SQL and PySpark for querying and analysis.

Caching & Distribution:

• Knowledge of Data Grid technologies like Hazelcast, Apache Ignite, or Redis.

Languages & Tooling:

• Advanced SQL skills including window functions and query optimization.
• Use of Python Pandas, Polars, and Scikit-learn for data wrangling and modeling.
• Skilled in architecting high-throughput ingestion pipelines using REST/WebSocket APIs and JSON-RPC.
• Strong ETL fundamentals and handling schema mismatches.

Engineering Mindset:

• Systematic debugging approach.
• Comfortable with large, semi-structured, or undocumented data sources.

• Maintain an AI-native and blockchain-forward mindset, leveraging emerging generative technologies.
• Architect intuitive data models transforming on-chain data into unified abstractions.
• Reverse-engineer DeFi protocols' smart contracts and on-chain events into production-grade SQL/dbt models.
• Lead indexing of new blockchains, designing schemas for accurate data capture.
• Define critical metrics such as TVL, Volume, and Fees and ensure data quality by filtering wash trading, bot activity, and Sybil attacks.