Related skills
snowflake python airflow kafka apache spark📋 Description
- Architect and implement high-scale data pipelines using Spark, Flink, and Airflow.
- Build data lakes with Snowflake, Iceberg, Parquet; ensure scalability and cost efficiency.
- Design robust data models for structured and semi-structured data for analytics.
- Develop real-time and batch pipelines with Kafka and Spark Structured Streaming.
- Automate ELT processes with Airflow; ensure reliability and observability.
- Create scalable data solutions on AWS (S3, Lambda, ECS).
🎯 Requirements
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
- 3+ years of data engineering experience with large-scale distributed data systems.
- Strong expertise in Snowflake and distributed analytical data stores.
- Hands-on with Apache Spark, Flink, Airflow, and modern data lakehouse formats (Iceberg, Parquet).
- Data modeling, schema design, query optimization, and partitioning strategies at scale.
- Proficiency in Python, SQL, Scala; Go/Node.js; debugging and performance-tuning skills.
🎁 Benefits
- Meaningful equity: Every "Safestar" is a shareholder.
- Unlimited paid leave.
- Comprehensive medical insurance and wellness benefits.
- Career growth and advancement opportunities.
- Culture of ownership and high-performance environment.
- Access to cutting-edge cybersecurity and data platforms.
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