Senior Data Engineer

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).