Baselayer is looking for an elite data engineer to design rock-solid infrastructure that powers cutting-edge AI/ML products, by building and maintaining scalable ETL/ELT pipelines and data infrastructure to support analytics and ML use cases.
Requirements
- 1–3 years of experience in data engineering, working with Python, SQL, and cloud-native data platforms
- built and maintained ETL/ELT pipelines
- comfortable with structured and unstructured data
- think in DAGs, love automating things with Airflow or dbt
- curious about AI/ML infrastructure
- value ethical data practices, especially when dealing with sensitive information in environments like KYC/KYB or financial services
- use tools like dbt
Responsibilities
- Design, build, and maintain robust, scalable ETL/ELT pipelines that power analytics and ML use cases
- Own the architecture and tooling for storing, processing, and querying large-scale datasets using cloud-based solutions (e.g., Snowflake, BigQuery, Redshift)
- Implement rigorous data quality checks, observability tooling, and alerting systems to ensure data integrity across environments
- Create efficient, reusable data models using tools like dbt, enabling self-service analytics and faster experimentation
- Continuously optimize query performance and cost in cloud data warehouses
- Stay on the cutting edge of data engineering tools, workflows, and best practices—bringing back what works and leveling up the team
- Partner with security and compliance teams to ensure data pipelines adhere to regulatory standards (e.g., SOC 2, GDPR, KYC/KYB)
Other
- Hybrid in SF. In office 3 days/week
- Flexible PTO
- Healthcare, 401K
- Smart, genuine, ambitious team
- translator between technical and non-technical stakeholders, aligning infrastructure with business outcomes
