SuperDial · 1 day ago
Data Engineering Lead
Burlingame, CA
Full-time
Onsite
Senior Level, Lead/Staff
$185K/yr - $240K/yr
2+ years expSuperDial is transforming AI in healthcare by building scalable, AI-powered solutions that optimize revenue cycle management. As Data Engineering Lead, you will own SuperDial’s data platform end-to-end, scaling the warehouse, pipelines, and analytics workflows that drive product decisions and company-wide planning.
Computer Software
Responsibilities
Own and scale SuperDial’s data warehouse and analytics stack
Lead development of robust dbt-based transformation layers that power trusted metrics
Design and maintain data pipelines that integrate product, GTM, and platform data
Manage and evolve data engineering workflows, orchestration, and dependencies
Partner with platform and product teams to support operational and analytical data needs, including performance-intensive use cases
Build clean, well-documented data models that serve as the source of truth across the business
Create high-impact dashboards and analyses that inform revenue, product usage, and customer behavior
Implement data quality checks, monitoring, and alerting to ensure reliable, decision-ready data
Establish best practices for modeling, testing, and analytics development as the company scales
Ramp on SuperDial’s product, data sources, and existing warehouse
Audit current dbt models, pipelines, orchestration, and reporting
Understand platform data needs and performance considerations
Ship early improvements to data quality, reliability, or documentation
Build strong relationships with Product, Platform, GTM, and Finance
Take full ownership of the data warehouse and analytics workflows
Improve or refactor core dbt models to support consistent metrics
Strengthen orchestration, testing, and monitoring across pipelines
Partner with engineering teams on platform-oriented data use cases
Deliver dashboards or analyses that materially improve decision-making
Establish a scalable data architecture and analytics engineering strategy
Proactively identify gaps in data availability, quality, or performance
Improve reliability and maintainability of data workflows end-to-end
Act as the go-to owner for data strategy and execution
Lay the groundwork for future platform-oriented or high-scale data systems
Qualification
Required
2+ years of experience in Analytics Engineering, Data Engineering, or BI Engineering roles
Deep hands-on experience with dbt, especially incremental models, and modern analytics engineering workflows
Very strong SQL skills and a track record of designing durable data models
Prior ownership of a production data warehouse in a scaling environment
Experience managing data pipelines, orchestration, and workflow dependencies
Proficiency with Python and orchestration tools such as Airflow or similar
Familiarity with cloud data platforms and infrastructure, and NoSQL databases (like Google Cloud Firestore, Mongo, etc.)
Strong ownership mindset with comfort driving ambiguous initiatives end-to-end
Clear communication skills and ability to partner with technical and non-technical stakeholders
Preferred
Experience working with high-performance or specialized data systems (e.g., ClickHouse or similar)
Benefits
Equity
Benefits as part of our total compensation package
Company
SuperDial
SuperDial automates high-volume outbound phone calls that healthcare teams make to insurers using advanced voice AI.
11-50 employees
Funding
Current Stage
Early StageLeadership Team
Sam Schwager
Co-Founder & CEO
Harrison Caruthers
Co-Founder & CTO
Recent News
2025-06-26
Seattle TechFlash
2025-06-25
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