About the Role
We are seeking an experienced professional to lead the development and optimization of our core data pipelines. The ideal candidate will have deep expertise in building scalable data architectures and improving data accessibility across teams.
Responsibilities
- Design and implement reliable data pipelines for large-scale applications
- Optimize data workflows to support real-time processing needs
- Ensure data accuracy, consistency, and availability across systems
- Collaborate with machine learning teams to integrate model outputs into data streams
- Monitor data pipeline performance and troubleshoot issues
- Develop and maintain documentation for data architecture and processes
- Support data governance and compliance standards
- Work closely with product and analytics teams to understand data requirements
- Improve data quality through validation and testing frameworks
- Evaluate and integrate new data storage and processing technologies
Nice to Have
- Experience in AI or machine learning data infrastructure
- Background in low-latency data systems
- Familiarity with streaming platforms like Kafka
- Prior work in fast-paced startup environments
- Contributions to open-source data projects
- Experience with data observability tools
- Knowledge of containerization and orchestration with Docker and Kubernetes
Compensation
Competitive salary and equity package
Work Arrangement
Hybrid remote
Team
Collaborative engineering team focused on scalable data systems
Why This Role Matters
The Senior Data Engineer plays a critical role in enabling AI-powered features by ensuring data is processed efficiently and made available with minimal latency. This position directly impacts product capabilities and scalability.
Technology Stack
We use modern data tools including BigQuery, Airflow, and Kafka, hosted primarily on Google Cloud Platform. Our systems are built for real-time data ingestion and processing to support dynamic AI workloads.
Available for qualified candidates
