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Nansen is an onchain analytics platform used by traders and funds to understand blockchain activity. The company labels and tracks 500M+ blockchain addresses—the largest dataset of its kind—and is building the data infrastructure that powers its customer-facing analytics product.
In this role, you'll design, build, and scale data pipelines and infrastructure using ClickHouse, Postgres, Python, and dbt. You'll manage the pipelines processing terabytes of streaming and batch data daily across 500M+ labeled addresses. You'll partner with crypto researchers, software engineers, and product teams to shape how data is modeled, surfaced, and productized.
Key responsibilities include owning data quality, reliability, and observability end-to-end—where data accuracy directly impacts customer trading decisions. You'll mentor other data engineers and raise the technical bar across the team. The role emphasizes using AI tools and agents to accelerate delivery and eliminate busywork.
You should have shipped and scaled high-performance data systems in production with deep expertise in SQL, Python, dbt, ClickHouse, and Postgres. You're comfortable with streaming data architectures at genuine scale and work across the full data stack: ingestion, transformation, storage, modeling, and serving. Experience with AI-assisted development tools (Cursor, Claude Code, MCPs) is expected. Strong written communication is essential for this remote, async-first team.
Bonus qualifications include project leadership experience in smaller teams, fluency in onchain data structures, and Web3/crypto market knowledge. The posting notes a clear path to Engineering Manager within 12–18 months for the right candidate.
