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aws python kubernetes hadoop airflow📋 Description
- Design, build and manage data pipelines integrated into the data warehouse.
- Develop canonical datasets to track product insights.
- Collaborate with customers to translate workflows into product experiences.
- Partner with Infrastructure, Data Science, Product, Marketing, and Research.
- Implement robust, fault-tolerant data ingestion and processing systems.
- Contribute to data architecture and engineering decisions.
🎯 Requirements
- 3+ years as a data engineer; 8+ years in software engineering.
- Proficiency in Python, Scala, or Java.
- Experience with Azure or AWS and tools like Kubernetes and Terraform.
- Experience with Hadoop, Flink, and storage systems such as HDFS/S3.
- ETL schedulers such as Airflow, Dagster, or Prefect.
- Solid understanding of Spark; write, debug and optimize Spark code.
🎁 Benefits
- Salary: USD 255K–325K per year.
- Equity: Offers equity.
- Location: San Francisco, on-site.
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