Nansen is a blockchain analytics platform that enriches on-chain data with millions of wallet labels. Crypto investors use Nansen to discover opportunities, perform due diligence and defend their portfolios with our real-time dashboards and alerts.

About the role

We’re looking for a Data Engineering Manager to join our 15 people strong Attribution team focused on labelling addresses in an efficient, accurate, and timely manner.

You’ll be instrumental in ensuring that we build and scale a world-class labelling machine, both by attracting, retaining, and growing talent, and by raising the bar on how data engineering contributes to our success as a team and as a company.

We need our data engineering managers to be versatile, display excellent leadership qualities, and be enthusiastic about taking on new problems across the organisation as we continue to push the crypto industry forward.

Responsibilities

• Enable our engineers to grow. Provide mentoring and coaching to employees in the team, helping them grow as professionals. Have frequent follow-ups on the goals and provide directions and mentorship to the employees
• Raise the bar for data engineering. Participate in code review to ensure the team is following high-quality data engineering standards around readability, testing, scalability, and performance. Drive technical decisions in the team by leveraging both senior and junior members, ensuring a healthy balance between an analytical and thorough approach.
• Contribute. Organises teamwork and priorities in order to meet commitments and deliver value increments at every iteration. Contribute to discussions around the overall Architecture of our engineering systems. Drives changes and improvements in the team's way of working
• Attract, recruit, and onboard data engineers. Participate in the hiring process for most data profiles

Are you the right person for this role?

The ideal candidate for us has:

• 3+ years of work experience as an Engineering Manager or similar role
• Passion for building great teams, products, and systems
• Excellent communication, both spoken and written
• Battle scars from leading technical projects and teams
• Bias towards action. You thrive making small iterations each and every day
• Proven track record of attracting and recruiting engineers, and enabling them to be great
• Extensive experience with building data pipelines, data models, and large-scale advanced analytics using tools such as BigQuery, Postgres, Airflow, Python, Kubernetes and dbt

The following are nice-to-haves:

• Knowledge and hands-on experience with Ethereum, crypto markets, and on-chain analytics
• Experience with building data products and start-ups