
High-Performance Data Processing Specialist
2 days ago
We are seeking a talented Big Data Engineer to join our team. As a Big Data Engineer, you will design, build, and maintain high-performance data pipelines that process terabytes of data.
Key Responsibilities:
- Design and implement scalable batch processing systems using Python and big data technologies
- Optimize database performance, focusing on slow-running queries and latency improvements
- Use Python profilers and performance monitoring tools to identify bottlenecks
- Reduce P95 and P99 latency metrics across our data platform
- Build efficient ETL pipelines that can handle large-scale data processing
- Collaborate with data scientists and product teams to understand data requirements
- Monitor and troubleshoot data pipeline issues in production
- Implement data quality checks and validation mechanisms
Qualifications Required:
- Bachelor's degree in Computer Science, Engineering, or related technical field
- 4+ years of experience in data engineering roles
- Strong Python programming skills with focus on data processing libraries
- Experience with big data technologies (Spark, Hadoop, etc.)
- Proven experience optimizing database performance (SQL or NoSQL)
- Knowledge of data pipeline orchestration tools (Airflow, Luigi, etc.)
Preferred:
- Master's degree in Computer Science or related field
- Experience with SEO data or web crawling systems
- Experience with Clickhouse Database
- Knowledge of distributed systems and microservices architecture
- Familiarity with container orchestration (Kubernetes, Docker)
Skills and Abilities:
- Strong analytical thinking and problem-solving skills
- Excellent attention to detail and commitment to data quality
- Ability to work effectively in a collaborative team environment
- Good communication skills to explain complex technical concepts
- Self-motivated with the ability to work independently
- Passion for performance optimization and efficiency
Our ideal candidate will have a strong background in big data technologies, data engineering, and software development.
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