Data Engineer Team Lead

Explorium is a cutting-edge data science company that has recently closed a Series C round bringing their total funding to $127 million.

Explorium offers a first of its kind data science platform powered by augmented data discovery and feature engineering. By automatically connecting to thousands of external data sources and leveraging machine learning to distill the most impactful signals, the Explorium platform empowers data scientists and business leaders to drive decision-making by eliminating the barrier to acquire the right data and enabling superior predictive power.

We are looking for a talented Data Engineering Team Lead with a passion for data and complex problems to lead the Data Onboarding Team.

As a Data Engineering Team Lead, you will lead a diversified engineering group, building a complex data product based on Spark, Airflow, DBT, OpenLineage, and more. 

You will have a key role in Explorium’s Data Organization, responsible for collecting, integrating, and serving high quality features for machine learning and analytical models. The team’s challenge is in the center of the company’s focus and growth, and this is an amazing opportunity to grow as an engineering leader. The position is 30-50% hands-on.


  • Lead a team of highly skilled senior engineers.
  • Work closely with data science and research teams to deliver high quality results to customers and partners.
  • Design and Implement complex end-to-end data products, taking ownership of the projects from POC to production.


  • Bsc in CS/Mathematics/Statistics/Physics/EE or equivalent experience.
  • 5+ years of industry experience working with large data sets with Spark, Ray, or alike.
  • 2+ years as a team leader, individual contributor, tech lead or architect.
  • Experience and understanding of data cloud environments, databases, warehouses, k8s, networking etc.
  • Experience designing and implementing data products from infrastructure to application, and a good understanding of tradeoffs.
  • Leader mentality - does not have to have management experience.
  • Experience with designing data lakes - advantage
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