Senior Data Engineer

📋 Description

• Own, maintain, and continuously improve change data capture (CDC) and data synchronization
• Optimize pipeline performance, scalability, and infrastructure efficiency by reducing processing
• Design, develop, and evolve data infrastructure by onboarding new data sources, tables, and markets
• Establish and maintain service level objectives (SLOs), implement monitoring and alerting
• Strengthen engineering standards by developing unit and integration tests, maintaining CI/CD
• Troubleshoot production incidents, lead root cause analyses, and translate findings into

🎯 Requirements

• At least 4 years of professional experience in backend engineering or data engineering, ideally
• Minimum 2 years of hands-on professional experience developing with Python.
• Proven ability to independently build, operate, troubleshoot, and optimize production-grade data
• Practical experience with change data capture (CDC) and stream processing technologies such as
• Strong proficiency in Apache Spark, particularly Spark Structured Streaming.
• Experience with modern data lakehouse architectures and table formats, including Apache Iceberg

🎁 Benefits

• Annual salary: $130,000–$200,000, depending on qualifications, experience, and other relevant
• Fully remote, remote-first working environment.
• Opportunity to collaborate with an international team across multiple global markets.
• Exposure to modern cloud infrastructure, AI-driven technology, and large-scale distributed data
• Opportunity to contribute to innovative financial technology solutions with meaningful global
• Inclusive and diverse working environment that values different backgrounds, perspectives, and