Baselayer is looking to solve the problem of verifying businesses, automating KYB, and monitoring real-time risk for 2,200+ financial institutions
Requirements
- 1–3 years of experience in data engineering, working with Python, SQL, and cloud-native data platforms
- Experience building and maintaining ETL/ELT pipelines
- Knowledge of clean, scalable data architecture
- Comfort with structured and unstructured data
- Experience with Airflow or dbt
- Familiarity with AI/ML infrastructure
- Experience with cloud-based solutions (e.g., Snowflake, BigQuery, Redshift)
Responsibilities
- Pipeline Development: Design, build, and maintain robust, scalable ETL/ELT pipelines that power analytics and ML use cases
- Data Infrastructure: Own the architecture and tooling for storing, processing, and querying large-scale datasets using cloud-based solutions (e.g., Snowflake, BigQuery, Redshift)
- Collaboration: Work closely with data scientists, ML engineers, and product teams to ensure reliable data delivery and feature readiness for modeling
- Monitoring & Quality: Implement rigorous data quality checks, observability tooling, and alerting systems to ensure data integrity across environments
- Data Modeling: Create efficient, reusable data models using tools like dbt, enabling self-service analytics and faster experimentation
- Security & Governance: Partner with security and compliance teams to ensure data pipelines adhere to regulatory standards (e.g., SOC 2, GDPR, KYC/KYB)
- Performance Optimization: Continuously optimize query performance and cost in cloud data warehouses
Other
- Highly feedback-oriented
- Proactive, ownership-driven, and unafraid of complexity—especially when there’s no playbook
- Hybrid in SF. In office 3 days/week
- Flexible PTO
- Healthcare, 401K
