Compensation: Up to $250,000 + Equity + Benefits
Location: Mountain View, CA (Hybrid)
DeepRec.ai have been tasked a Data Infrastructure Engineer to take ownership of the company’s analytics backbone — from warehouse design through to integration, performance, and data reliability. This role will play a key part in enabling company-wide insight and analysis through well-structured, secure, and scalable systems.
You’ll lead initiatives around warehouse architecture, define data models that support reporting and research, and work across teams to ensure data flows accurately and efficiently. This role suits someone who enjoys designing systems from the ground up and takes pride in robust, well-documented engineering work.
Responsibilities:
- Design and deploy a scalable data warehouse to support analytics and business intelligence.
- Define data models and schemas that serve a wide range of use cases across engineering and product.
- Develop and maintain ETL/ELT pipelines to ensure data completeness and integrity.
- Monitor performance, optimise queries, and maintain healthy data infrastructure.
- Work closely with stakeholders to define data requirements and deliver solutions that support them.
- Enforce standards around data governance, access control, and compliance.
- Maintain high-quality documentation and contribute to long-term data architecture planning.
- 10+ years of experience in data engineering, data architecture, or analytics infrastructure.
- Strong experience with warehouse technologies (e.g. BigQuery, Snowflake, Redshift).
- Fluency in SQL and familiarity with relational databases (e.g. Postgres, MySQL).
- Experience with ETL frameworks and tools (e.g. Airflow, dbt, Talend, or Apache NiFi).
- Familiarity with cloud services and infrastructure (AWS, GCP, or Azure).
- Strong problem-solving abilities and the ability to work independently or cross-functionally.
