
Data Infrastructure Architect
2 days ago
We're seeking an experienced Big Data Engineer to join our team. As a key member, you'll design and build high-performance data pipelines that process massive amounts of data.
Key Responsibilities:
- Design 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.
- Document data architecture and engineering processes.
- Stay current with emerging big data technologies and best practices.
Qualifications:
- 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.).
- Understanding of performance optimization techniques and profiling tools.
- Experience with cloud platforms (AWS, GCP, or Azure).
- Ability to translate business requirements into technical specifications.
- Ability to work in a collaborative team environment.
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.
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