About the Role
The role involves designing and maintaining robust data pipelines, leading technical initiatives, and mentoring engineers while working closely with cross-functional teams to deliver high-quality data infrastructure.
Responsibilities
- Lead the architecture and implementation of data ingestion pipelines
- Ensure data collection systems are scalable and fault-tolerant
- Collaborate with product and data teams to define data requirements
- Design and deploy ETL workflows for structured and unstructured data
- Monitor system performance and troubleshoot data flow issues
- Implement data validation and quality assurance processes
- Guide best practices in software development for the engineering team
- Mentor junior engineers in coding standards and system design
- Evaluate and integrate new data collection technologies
- Maintain documentation for data pipelines and system architecture
- Support compliance with data privacy and security standards
- Optimize data transfer efficiency across distributed systems
- Work with cloud infrastructure for data storage and processing
- Drive automation of repetitive data operations
- Coordinate with stakeholders to prioritize technical deliverables
- Contribute to code reviews and system testing procedures
- Ensure high availability and low-latency data access
- Develop APIs for internal data sharing
- Improve monitoring and alerting for data pipelines
- Lead incident response for data system outages
Nice to Have
- Master’s degree in computer science or related field
- Experience in cybersecurity or risk analytics domains
- Contributions to open-source data engineering projects
- Knowledge of data lineage and metadata management
- Experience with stream processing frameworks
- Background in incident response systems
- Familiarity with regulatory compliance frameworks
- Leadership in cross-functional technical initiatives
- Published technical papers or conference talks
- Experience mentoring engineers in remote settings
Compensation
Competitive salary and benefits package
Work Arrangement
Hybrid work model with flexible remote options
Team
Collaborative engineering team focused on scalable data systems
About the Team
This team specializes in building resilient data infrastructure to support analytics and risk modeling. Engineers work on high-impact systems that process diverse data sources at scale.
Technology Stack
The team uses Python, Kafka, AWS, Docker, Kubernetes, PostgreSQL, and Spark to manage and process large volumes of structured and unstructured data.
Available for qualified candidates
