Related skills
dynamodb sql s3 python hadoop📋 Description
- Own and scale the core data pipeline to handle Lyft's data growth
- Evolve data models and schemas to meet business needs
- Implement systems for data quality and consistency
- Build tools for self-service ETL and data pipelines
- Tune SQL engines and MapReduce jobs for performance
- Write clean, tested, maintainable code
🎯 Requirements
- 4+ years in data engineering with large-scale distributed systems
- Strong experience with Spark
- Hadoop ecosystem, S3, DynamoDB, Hive, Parquet
- Scripting in Python or Go
- SQL engine understanding and performance tuning
- Experience with workflow tools (Airflow, Oozie, Azkaban)
🎁 Benefits
- Stable working environment
- Latest tech and equipment
- Potential for remote work internationally
- 28 days vacation
- 18 weeks paid parental leave
- Mental health and family benefits
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