Key skills
Distributed SystemsGRPCPandasPySparkPythonData EngineeringDatabricksgRPC
About this role
Role Overview
- Design, implement, and maintain backend services and data pipelines using Python
- Work extensively with dataframes (Pandas, PySpark, or similar) to process large datasets
- Build and optimize data pipelines using Parquet and columnar storage formats
- Develop and maintain workflows on Databricks
- Optimize performance for large-scale, distributed data processing
- Design and maintain APIs that support data-heavy applications
- Collaborate closely with front-end, data, and product teams
- Ensure data quality, reliability, and observability
- Participate in architectural decisions and technical planning
- Mentor other engineers and lead code reviews
Requirements
- 5+ years of backend or data engineering experience
- Strong proficiency in Python
- Deep experience with dataframes (Pandas, PySpark, Dask, or similar)
- Hands-on experience with big data processing and distributed systems
- Strong experience working with Parquet and columnar data formats
- Experience using Databricks in production environments
- Solid understanding of data modeling, performance tuning, and memory optimization
- Experience building and maintaining APIs (REST and/or gRPC)
- Strong debugging, testing, and problem-solving skills
Tech Stack
- Distributed Systems
- GRPC
- Pandas
- PySpark
- Python
Benefits
- Annual Bonus
- Medical, Vision, Dental, 401(k)
- 21 Days Vacation
- Office Lunch provided Daily