Senior Data Engineer
1 week ago
We are seeking a skilled Senior Data Engineer with deep expertise in ClickHouse and streaming data, and a passion for building scalable real-time analytics solutions. In this role, you will design, develop, and optimize our data pipelines and analytics infrastructure, empowering our teams to harness real-time insights that enhance customer experience and drive business growth.
Key Responsibilities
- Design, implement, maintain and document highly scalable data pipelines for real-time and batch processing.
- Build and optimize data systems to support accurate, low-latency analytics and reporting use cases.
- Develop and maintain solutions for streaming and serverless data processing.
- Collaborate with cross-functional teams to implement and support end-to-end analytics workflows.
- Ensure data quality, reliability, and performance across the platform.
- Monitor, troubleshoot, and optimize data infrastructure to maintain high availability.
- Mentor junior engineers and contribute to the continuous improvement of engineering practices.
- Strong problem-solving skills and the ability to thrive in a fast-paced environment.
- Excellent communication and teamwork skills.
Requirements
5+ years of experience in Data Engineering or related fields.
Strong expertise in ClickHouse (schema design, ingestion optimization, query performance tuning, and cluster management).
- Proven experience with real-time data processing using Apache Kafka, Flink, or Spark Streaming.
- Deep understanding of distributed systems architecture with emphasis on scalability, reliability, and fault tolerance.
- Proficiency in one or more programming languages:
Python: Building data pipelines, automation scripts, and integrations.
Go: Developing high-performance data services or tools.
TypeScript: Contributing to data-related front-end or service-side applications.
Bash/Shell scripting: Writing automation scripts for data operations.
Rust (Good to have): Interest or experience in building memory-safe, high-performance systems.
- Hands-on experience with cloud platforms such as AWS, GCP, or Azure.
- Familiarity with containerization and orchestration tools (Docker, Kubernetes).
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