Lume Finance is hiring a
Data Engineer (Blockchain & Analytics)

Compensation: $84k - $150k estimated

Location: Remote

Role Overview:

Data Engineer who can efficiently fetch, structure, and manage blockchain data from The Graph and other sources. You will be responsible for setting up ETL pipelines, transforming raw blockchain data into structured formats, and making it accessible for backend APIs and internal analytics. Your work will empower our backend developers to build efficient APIs and enable meaningful data visualizations for users.

Key Responsibilities:

  • Fetch and process blockchain data from The Graph and other sources.
  • Design and implement ETL (Extract, Transform, Load) pipelines to structure raw data.
  • Store and optimize data for efficient querying and API consumption.
  • Identify patterns, trends, and insights from blockchain data to enhance analytics.
  • Ensure data integrity, consistency, and performance in a scalable architecture.
  • Work closely with the backend team to provide well-structured data for APIs.
  • Optimize database performance for real-time and historical analytics.
  • Implement caching, indexing, and aggregation strategies for large-scale data processing.

Required Skills & Experience:

  • Strong experience with The Graph (GraphQL queries).
  • Expertise in ETL processes and data pipeline management.
  • Experience with data modeling and structuring for analytics & API consumption.
  • Proficiency in Python, Node.js, or Rust for data processing.
  • Knowledge of database management (SQL, NoSQL, time-series DBs, or data lakes).
  • Ability to detect patterns and trends in blockchain transaction data.
  • Experience handling large-scale datasets efficiently.

Nice to Have:

  • Experience with blockchain indexing beyond The Graph (custom indexers, RPC data extraction).
  • Prior experience in financial or DeFi data analytics.
  • Familiarity with machine learning for pattern detection in financial transactions.

Apply Now:

Compensation: $84k - $150k estimated

Location: Remote


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