Data Team Lead at ConsenSys

What You’ll Do

• As the Data lead, you will manage Infura’s data team consisting of Analysts, Data Scientists, and Data Engineers.
• This is a leadership role so you will use your deep experience managing people to help grow our data talent and mature our data capabilities.
• This role encompasses 2 sides of the data organization: the analysis side (including data science) and the engineering side.
• As an engineering lead, you will oversee the development and maintenance of a high quality data platform from which multiple stakeholders in the company can build their insights.
• As an analytics lead, you will help lead and structure the analysis of data into a collection of data products that foster an empowered / self-service data culture at Consensys.
• The role comprises three main areas of responsibility: the data roadmap, data governance, and engineering culture.
• In managing the roadmap, the data lead will ensure that all commitments are reasonable and achievable.
• They will work with the analytics and engineering teams to sequence out and deliver all data products and analytics reports.
• Managing the governance of the data team involves establishing and maintaining the classification of all data managed by Infura, aligning with compliance requirements, and ensuring the data lifecycle is adhered to. Managing the engineering culture of the team will involve establishing and implementing best practices, incorporating principles of software engineering, and ensuring the continuity of engineering excellence within the data engineering team.
• The data lead will manage multiple stakeholder relationships both internal to Infura as well across the Consensys organization.

Would be great if you brought this to the role

• You have at least 5-7 years of experience leading complex projects.
• You have 3-5 years of experience managing people.
• You have a deep understanding of servant leadership and have had success growing the skills of your past teams.
• You come from an engineering background and have shaped the engineering culture of past teams.
• You have hands-on experience with systems in our data stack including Redshift, Airflow, EMR / Pyspark, streaming systems like Kinesis, and Data Lake implementations.
• An understanding of various analytics methodologies and how data products feed into end user analytics will enable you to effectively manage the analytics side of the team.