Staff Analytics Engineer
Summary
Builds and owns data models in Snowflake/Databricks, designs ML pipelines, and integrates new data sources to power real-time analytics and AI features for a product-focused company.
Responsibilities
- Create and own key data models in data warehouse
- Pioneer new tools and technologies for advanced analytical features
- Integrate fresh data sources for machine learning pipelines
- Collaborate with business and engineering teams for scalable architecture
- Manage ELT pipelines for reporting systems
- Guide product and engineering teams for analytics and ML requirements
Qualifications
- 5+ years of experience in analytics or data engineering
- Strong technical background with a love for complex projects
- Deep expertise in data modelling and transformation
- Hands‑on experience using tools like dbt
- Cloud data warehouse experience using platforms like Snowflake or Databricks
- Track record of building ML features for real‑time applications
- Strong tool‑evaluation skills for AI and ML readiness
- Broad programming knowledge
- Exposure to real‑time streaming frameworks like Apache Flink (insurance domain knowledge is a plus)
Core Competencies
Demonstrates expertise in data modeling, transformation, and integration for machine learning pipelines, with a strong focus on building scalable architectures and advanced analytical features. Proficient in managing ELT pipelines and collaborating with cross‑functional teams to drive analytics and machine learning initiatives.