About the Role
The Data Engineering Lead will oversee the architecture and operation of data infrastructure, enabling efficient data access and insights across the organization while leading technical strategy and team development.
Responsibilities
- Design and implement robust data pipelines for efficient data ingestion and processing
- Lead the development and maintenance of data warehousing solutions
- Ensure data accuracy, consistency, and accessibility across systems
- Collaborate with data scientists and analysts to understand data needs
- Optimize data workflows for performance and scalability
- Enforce data governance and security standards
- Mentor and guide junior engineers in best practices and technical execution
- Evaluate and integrate new data technologies and tools
- Monitor data system performance and troubleshoot issues
- Support the migration of legacy data systems to modern architectures
- Work closely with product teams to align data infrastructure with business goals
- Define and document data models and pipeline architectures
- Implement automated testing and monitoring for data pipelines
- Drive initiatives to improve data quality and reliability
- Participate in architectural reviews and technical planning sessions
Nice to Have
- Experience with real-time data streaming technologies such as Kafka
- Knowledge of machine learning pipeline integration
- Prior work in startup or fast-paced technology environments
- Contributions to open-source data projects
- Advanced degree in a technical discipline
Benefits
- Health and wellness insurance coverage
- Flexible working hours and remote options
- Professional development budget
- Annual team offsite and company retreats
- Stock options as part of compensation package
- Generous vacation and personal time policy
- Parental leave and family support programs
- Onsite or subsidized fitness memberships
- Employee assistance and mental health resources
- Inclusive and diverse workplace culture
Compensation
Competitive salary with performance-based incentives
Work Arrangement
Hybrid work model with flexibility for remote and office-based work
Team
Collaborative environment within a cross-functional product and engineering team
Our Tech Stack
- We use Apache Airflow for workflow orchestration
- Data processing is powered by Apache Spark on Google Cloud Platform
- Our primary data warehouse is BigQuery
- We rely on Kafka for event streaming and real-time data
- Infrastructure is managed using Terraform and deployed via CI/CD pipelines
Growth Opportunities
- Opportunities to shape the data platform from the ground up
- Direct impact on product and business strategy through data
- Leadership roles in expanding data and analytics teams
- Regular tech talks and knowledge-sharing sessions
- Support for conference attendance and certifications
Available for qualified candidates requiring work authorization
