You will be responsible for designing, building, and optimizing complex data pipelines to process transactional and other data. You will collaborate closely with data scientists and analysts in developing and maintaining data solutions and the company’s data architecture to support the next generation of products and data initiatives. We are looking for curious and empathetic individuals who are committed to developing themselves and learning new skills. We hire people based on an evaluation of their potential and support them throughout their time.

• Experience with Phyton and PySpark or Spark
• Experience with deployment and provisioning automation tools.
• Experience with monitoring and observability (ELK stack).
• Knowledge of MLOps architecture and practices.
• Knowledge of data manipulation and transformation.  

• Bachelor's degree or equivalent practical experience.
• At least 5 years of relevant expereince
• Excellent communication skills, capable of working collaboratively in a semi remote, globally distributed team.
• Hands-on experience building complex data pipelines (e.g., PySpark, Airflow).
• Comfortable with Python and SQL.
• Experience designing data models, and using SQL database management systems, along with data processing using traditional and distributed systems.
• Knowledge of software engineering best practices and tools (e.g., CI/CD tools, testing).  
• Willing to work on a Hybrid (1-2x per week), day shift schedule.