Data Engineer (Blockchain Data)

Role overview Build a data warehouse that brings payment decisions, settlement records and blockchain activity together. The data will support precise finance reporting and, over time, risk models that can assess spending while a payment is being considered.

Responsibilities - Create pipelines joining backend settlement records with Base and Solana transaction histories for paid addresses; backfill historical data and keep it current. - Build exportable spend reports that break down payments by agent, policy, counterparty and chain, reconciling amounts to settlement records at USDC’s sixth decimal place. - Prepare features and training datasets for models that identify unusual spending, with data fresh enough to inform payment decisions. - Design the warehouse so additional networks, including Ethereum, Arbitrum and Polygon, can be added without rebuilding the system.

Requirements - Practical experience writing SQL and Python, including code used in production. - Experience working with blockchain data from sources such as nodes, indexers, explorer APIs or analytics dashboards; a public dashboard can demonstrate relevant work. - Residence in a country where the organization can hire. - Relevant work can come from employment, open source, hackathons or personal projects; prior job title need not match.

Nice to have - Experience building subgraphs or blockchain analytics transformations. - Familiarity with dbt, Spark, Snowflake, BigQuery or ClickHouse. - Experience with streaming systems such as Kafka or Flink, or finance reporting approved for operational use.

Benefits and work setup The stated US salary range is $150,000–$200,000; offers elsewhere are benchmarked to the local market and paid in USD, with USDC as an option. The package includes vesting equity, health coverage or a contribution toward private cover, 25 vacation days plus public holidays, a year-end closure, 14 weeks of paid parental leave, a laptop and workspace allowance, and an annual learning budget. Hours are flexible, with a shared team availability window of 14:00–17:00 UTC; adjustments can be discussed when that timing is impractical. A compatible second job is permitted.