Blockchain Data Analyst, Researcher

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Lukka

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2014

💳 Fintech

₿ Crypto

☁️ SaaS

Fintech • Crypto • SaaS

Lukka is a global leader in institutional-grade digital asset data, software, and compliance. The company provides enterprise data management, blockchain analytics, and custom SaaS solutions tailored specifically for funds, financial institutions, crypto-native businesses, CPAs, and government agencies. With a focus on accuracy and reporting, Lukka's solutions facilitate effective management and compliance in the rapidly evolving crypto ecosystem.

📋 Description

• Maintain an AI-native and blockchain-forward mindset, proactively leveraging emerging trends and generative technologies to stay at the vanguard of the crypto revolution while maximizing work efficiency and uncovering novel, high-alpha data opportunities. • Architect Intuitive Data Models: Turn the messiness of on-chain data into elegant, unified abstractions. • Deconstruct DeFi Mechanics: Get under the hood of DeFi protocols. You'll reverse-engineer smart contracts and on-chain events, translating complex interactions into clean, production-grade SQL/dbt models. • Scale Our Ecosystem Coverage: Lead the charge in indexing new blockchains. You’ll design the schemas that transform raw chain data into our internal "source of truth," ensuring every block is captured with 100% accuracy. • Engineer Signal from Noise: Define the metrics that matter (TVL, Volume, Fees). You’ll be the gatekeeper of data quality, proactively identifying and filtering out wash trading, bot activity, and Sybil attacks.

🎯 Requirements

• 3+ years hands-on in Data Science, Data Engineering, or a hybrid role • Blockchain or crypto analytics background strongly preferred, familiarity with on-chain data structures, transaction semantics, and asset classification • Streaming & Lakehouse Apache Flink or Spark Streaming building and operating real-time data pipelines • Apache Iceberg or Apache Hudi managing large-scale Data Lakehouses with schema evolution, time travel, and ACID guarantees over petabytes of raw blockchain data • AWS Data Platform S3 for scalable data lake storage • RDS for structured relational workloads • Spark SQL and PySpark for interactive querying and ad-hoc analysis • Familiarity with Data Grid technologies (e.g. Hazelcast, Apache Ignite, Redis) for high-throughput, low-latency data access patterns • SQL advanced query writing, window functions, query plan analysis, performance tuning at scale • Python Pandas, Polars for data wrangling • Scikit-learn for model development • Proficient in architecting high-throughput ingestion pipelines that leverage external data sources REST/WebSocket APIs, JSON-RPC node queries • Strong grasp of ETL fundamentals (extract, transform, load), including managing schema mismatches between heterogeneous sources and destinations • Systematic approach to debugging: reproducing issues, isolating root cause, validating fixes • Comfortable working with large, semi-structured, or undocumented data sources.

🏖️ Benefits

• opportunity to work directly on data for digital assets, an industry-leading product with well-known clients. • working with multiple AI solutions daily. • exposure to both technical problem-solving and customer-facing challenges. • a growing Poland-based team with direct collaboration across US and global stakeholders. • a startup-style culture where your impact is visible every day.