Minimum qualifications:

• Bachelor’s degree in a quantitative or technical field (e.g., Computer Science, Statistics, Mathematics, Engineering), or equivalent practical experience.
  
• 3 years of experience in data engineering or business intelligence roles contributing to a shared codebase.
  
• 3 years of experience in system design or in a programming language (e.g., Java, C++, Python, etc.).
  
• Experience with relational databases, including writing and optimizing SQL queries and designing schema.
  

Preferred qualifications:

• Experience using SQL in a large-scale investigative, NoSQL, columnar context.
  
• Experience using continuous integration and deployment systems (e.g., Cloud Build, GitLab, Jenkins).
  
• Experience writing unit tests (e.g., PyTest, Selenium, JUnit).
  
• Knowledge in Machine Learning (ML).
  
  Responsibilities
  
  
  • Build, optimize, and maintain data infrastructure including large-scale data processing pipelines (e.g., ETL; BigQuery, Snowflake, Redshift or Dataflow, Beam, Spark Jobs), Machine Learning (ML) model training/tuning (e.g. AutoML) and inference pipelines and orchestration workflows (e.g., Cloud Composer, Airflow, Prefect).
  • Advocate for engineering best practices within the team and outside of it by writing and reviewing technical documentation, writing highly-readable and style-conformant code, and leading training.
  • Comply with complicated and ever-changing policy and governance requirements.