About the Role
Design and implement robust data pipelines and storage solutions that enable reliable access to high-quality data for analytics, reporting, and AI systems.
Responsibilities
- Develop and maintain core data infrastructure used across departments
- Ensure data accuracy, consistency, and accessibility enterprise-wide
- Collaborate with analytics and machine learning teams on data needs
- Design scalable ETL workflows for structured and semi-structured data
- Optimize data storage architectures for performance and cost
- Define and enforce data modeling standards and best practices
- Support data governance and compliance initiatives
- Troubleshoot and resolve data quality issues proactively
- Evaluate and integrate new data technologies and tools
- Document systems and processes for internal knowledge sharing
- Work closely with product teams to understand data requirements
- Improve monitoring and observability of data pipelines
- Contribute to capacity planning for data growth
- Mentor junior engineers and promote technical excellence
- Participate in design reviews and architectural decisions
- Maintain high standards for system reliability and uptime
- Automate repetitive data operations and deployment tasks
- Ensure security protocols are followed in data handling
- Collaborate on disaster recovery and backup strategies
- Drive improvements in data processing efficiency
Nice to Have
- Master’s degree in computer science or related field
- Experience with machine learning pipeline infrastructure
- Contributions to open-source data projects
- Public speaking or conference presentations
- Leadership in data strategy initiatives
Compensation
Competitive salary and equity package
Work Arrangement
Hybrid remote with team collaboration expectations
Team
Part of a growing data platform team focused on scalable systems
Our Data Philosophy
We believe data should be trusted, accessible, and actionable. Our platform emphasizes self-service capabilities while maintaining strong governance and security standards. Engineers focus on enabling data-driven decisions across product, risk, and operations teams.
Technology Stack
- Primary cloud provider is Google Cloud Platform
- Data warehouse: BigQuery
- Orchestration: Apache Airflow
- Programming languages: Python, SQL
- Version control: GitHub
- Infrastructure as code: Terraform
Available for qualified candidates
