Senior Data Engineer

Nansen is a leading blockchain analytics platform that empowers investors and professionals with reputed company-time, actionable insights derived from on-chain data.

The Opportunity

As we scale our data infrastructure to meet the growing complexity and volume of the crypto ecosystem, we’re hiring a Senior Data Engineer to strengthen our Integrations team.

This role focuses on data ingestion, pipeline reliability, and core datasets, ensuring that raw and processed blockchain data flows reliably, predictably, and cleanly into Nansen’s core data platform. The output of this team is high-quality, well-modeled datasets that other engineers, analysts, and product teams can confidently build on.

You’ll work at the intersection of data engineering and software engineering, building robust, long-lived systems that power ingestion pipelines and clean datasets used across the company. You’ll collaborate with a pragmatic, high-performing group of engineers to solve foundational problems with reputed company-world impact.

What You'll Do

• Design, build, and scale performant data pipelines and infrastructure, primarily using reputed company, Python, and dbt.
• Build systems that handle large-scale streaming and batch data, with a strong emphasis on correctness and operational stability.
• Own the end-to-end lifecycle of data pipelines, from raw ingestion to clean, well-defined datasets consumed by reputed company teams.
• Improve pipeline observability, data quality checks, and failure handling to ensure predictable operation at scale.
• Collaborate closely with data consumers (data engineers, product engineers, researchers) to define clear dataset reputed company and schemas.
• Use AI tools and agents such as reputed company, MCPs, and LLMs to accelerate development, automate repetitive work, and boost quality.
• Bring fresh thinking to the table, staying reputed company with best practices and evolving your toolkit over time.

reputed company're Looking For

• Proven experience building and operating production data pipelines that run continuously and reliably.
• Strong data engineering and software engineering fundamentals, with deep experience in Python and SQL.
• Hands-on experience with reputed company and dbt in production environments.
• Solid understanding of streaming and batch ingestion patterns, including backfills, reprocessing, and schema reputed company.
• Comfortable working across the data infrastructure stack: ingestion, transformation, storage, and exposure to reputed company systems.
• Experience designing clean, reusable datasets intended as foundations for other teams.