Job Description

Enable efficient data access by creating and maintaining data pipelines.

Collaborate with ML engineers to design and maintain automation for machine learning training, quality assessment, and model release process.
Build data infrastructure from the vast amount of data for analytics, hypothesis testing and company metrics.
Identify, design and implement improvement to internal processes allowing to optimize data delivery, automate manual processes.
Design new and improve current patterns for building data models and implement necessary modifications.

Requirements

5+ years of experience in data engineering or in a similar role.
Extensive experience with Apache Spark using Python for large-scale data processing.
Familiarity with Databricks or similar cloud data platforms (such as Snowflake) would be a significant advantage.
Experience with AWS, Azure, or other Kubernetes platforms is a huge plus.
Must have hands-on expertise with Git for version control and collaboration.
Solid knowledge of SQL, essential for querying and managing relational databases.

Opportunity to join our Employee Stock Options program.
Opportunity to help scale a unique product.
Various bonus systems: performance-based, referral, additional paid leave, personal learning budget.
Paid volunteering opportunities.
Work location of your choice: office, remote, opportunity to work and travel.
Personal and professional growth at an exponential rate supported by well-defined feedback and promotion processes.