We are looking for a Senior Data Engineer to join and help lead our Big Data team. In this role, you will take ownership of end-to-end data pipelines—from ingestion to analytics—and help architect and evolve our data platform to handle large-scale, production-grade workloads.

Responsibilities:

• Design, build, and optimize scalable batch and streaming data pipelines using Apache Spark and Kafka
• Define and evolve the architecture of our data platform based on business and technical needs
• Own data modeling and schema design for analytics in ClickHouse and other OLAP systems
• Lead the implementation of data quality, monitoring, and governance practices
• Contribute to the setup and tuning of data lake storage (e.g., MinIO/S3)
• Orchestrate workflows using Apache Airflow, ensuring reliability and maintainability
• Work with analysts and business users to ensure data accessibility and usability via BI tools like Superset
• Review code, mentor team members, and contribute to documentation and technical standards
• Stay up-to-date with trends in data infrastructure and recommend improvements
• Help ensure the system can reliably handle multi-terabyte scale data ingestion and processing

Requirements:

• 5+ years of experience in data engineering, with a strong portfolio of production systems
• Deep understanding of distributed data processing (preferably using Apache Spark)
• Production experience with Apache Kafka for real-time or near-real-time data ingestion
• Strong proficiency in Python / Scala, and advanced SQL
• Experience with columnar databases such as ClickHouse or similar OLAP solutions
• Familiarity with S3-compatible object storage (e.g., MinIO) and file formats like Parquet
• Comfortable designing data pipelines in self-hosted and Linux-based environments
• Experience with workflow orchestration tools like Apache Airflow
• Strong communication skills and a collaborative mindset