Responsibilities
- Lead end-to-end data engineering initiatives, from design and development to deployment and transition to operations.
- Create robust, scalable data models and lakehouse architectures, applying medallion zone patterns when applicable.
- Continuously improve system efficiency and reduce cloud spending, taking direct accountability for compute costs in Databricks and underlying infrastructure.
- Manage data pipelines and workflows using Databricks Workflows, Delta Live Tables, or similar technologies.
- Enforce data governance, security, monitoring, and lineage using Unity Catalog, and establish CI/CD practices for data assets.
- Build data platforms that support advanced analytics, machine learning, and autonomous AI applications.
- Collaborate directly with clients to understand business needs and convert them into technical implementations.
- Conduct code reviews, guide junior team members, and uphold high standards of engineering quality across projects.
- Develop and share reusable tools, frameworks, and best practices to strengthen organizational capabilities.
Compensation
Competitive base salary with performance-based bonuses
Work Arrangement
Remote-first work environment
Team
Small pods of A-players, heavy internal AI leverage, no bloated middle layers
Other
- Databricks certification is preferred; if not already held, candidates are expected to obtain a relevant certification (e.g., Data Engineer Associate/Professional) after joining.
- Provision of a MacBook Pro and onboarding kit to support effective remote work
- Ample time off, flexible PTO policy, and a remote-first workplace
- Dedicated budget for professional growth, including certifications in Databricks and cloud platforms
- One-time bonuses for earning relevant technical certifications
- Opportunities to attend conferences and contribute to industry thought leadership
