About the Role
The role involves building and maintaining scalable data infrastructure to support high-throughput transaction processing and analytics. The engineer will work closely with cross-functional teams to optimize data pipelines, improve system reliability, and implement monitoring solutions for critical platform components.
Responsibilities
- Design and implement scalable data pipelines for real-time transaction processing
- Optimize data storage and retrieval systems for low-latency access
- Collaborate with product and analytics teams to define data requirements
- Ensure data consistency and integrity across distributed systems
- Monitor and troubleshoot production data workflows
- Improve reliability and observability of data platform components
- Evaluate and integrate new data technologies and frameworks
- Write clean, maintainable code with thorough testing practices
- Support incident response and root cause analysis for data issues
- Document system architecture and data flow patterns
- Contribute to capacity planning for data infrastructure
- Implement data quality checks and validation layers
- Work with security teams to enforce data access controls
- Refactor legacy systems to improve scalability and maintainability
- Participate in code and design reviews
- Drive best practices in data modeling and schema design
- Assist in on-call rotations for critical data services
- Optimize query performance across large datasets
- Support compliance and audit requirements for financial data
- Collaborate on disaster recovery planning for data systems
Nice to Have
- Experience with real-time fraud detection systems
- Background in financial technology or payments infrastructure
- Knowledge of stream processing frameworks like Flink or Spark Streaming
- Familiarity with time-series databases
- Experience with data governance and lineage tools
- Contributions to open-source data projects
- Advanced degree in computer science or engineering
- Experience with regulatory compliance in financial services
Compensation
Competitive salary with equity and benefits
Work Arrangement
Remote-friendly with flexibility for time zones
Team
Collaborative engineering team focused on data infrastructure
Tech Stack
- Primary languages: Go, Python
- Data infrastructure: Kafka, Flink, BigQuery, PostgreSQL
- Cloud: AWS (EC2, S3, Lambda, CloudWatch)
- Orchestration: Kubernetes, Terraform
- Monitoring: Prometheus, Grafana, Datadog
Impact
- Engineers directly influence platform scalability and reliability
- Work impacts real-time transaction decisioning and risk systems
- Data platform supports company-wide analytics and reporting
- Projects contribute to low-latency financial data processing
Available for qualified candidates
