Data Quality Engineer (Attribution)

  • 🎯 Nansen’s mission is to surface the signal in blockchain data.
  • 💻Our core product is a SaaS analytics platform used by investors, crypto teams, and analysts.
  • 🌏Our company HQ is in Singapore, but team members are located all over the world.
  • 🙌We have an open and friendly work environment: every person helps shape our culture.
  • 🌱It's important for us that every individual in the team experiences personal growth.

About the role

As a Data Quality Engineer you would be a crucial member of our 8 person Attribution Team, working towards attaining the deepest knowledge of behaviour on Ethereum and EVM chains.

Quality is very important to us and the Nansen community, and your contributions to the team will therefore have a big impact.

You can be located anywhere in the world, as our work is 100% online.

The position is full-time.

What will you be doing?

You will be responsible for maintaining and measuring data quality in our Attribution datasets. This includes:

  • Taking initiative and being responsible for data quality processes
  • Defining and maintaining automated tests to continuously monitor data quality
  • Designing, developing and supporting various data pipelines in both batch and streaming modes
  • Collaborating with and influencing stakeholders to ensure our data quality meets constantly evolving requirements
  • Writing and reviewing technical documentation and specifications used by the whole team

Are you the right person for this role?

The ideal candidate for us has:

  • 3+ years work experience as a data quality engineer, software quality engineer or similar role
  • direct experience with the crypto markets (either professionally or as a hobby)
  • experience designing data models and data warehouses and using SQL
  • experience with API testing
  • an eye for detail, but is pragmatic and able to get things done fast
  • an ability to self-organize in a remote-first work environment
  • experience with BigQuery, dbt and Python

Ready to apply?

Please send an email to and include:

  1. Brief text on why you're the right candidate for this role
  2. Tell us about your relevant experience
  3. CV (or link to Linkedin profile)