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Data Engineering Lead

SuperDial · Remote, United States

Data Science / AI / Machine LearningLeadRemoteQuick applyfull-time5 months ago

About The Role

Overview

Application

As Data Engineering Lead, you will own SuperDial’s data platform end-to-end. You will be responsible for scaling the warehouse, pipelines, and analytics workflows that power product decisions, go-to-market execution, and company-wide planning.

This role is ideal for someone with a strong analytics engineering foundation who has grown into data platform ownership and wants to operate as a true lead, leveraging data analytics and insights proactively to help shape the direction of SuperDial.

About the Role

  • 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

30 / 60 / 90 Day Expectations

30 Days

  • 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

60 Days

  • 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

90 Days

  • 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

About You

  • 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.)
  • Experience working with high-performance or specialized data systems (e.g., ClickHouse or similar) is a plus
  • Strong ownership mindset with comfort driving ambiguous initiatives end-to-end
  • Clear communication skills and ability to partner with technical and non-technical stakeholders

Why SuperDial

  • True ownership over the company’s data and analytics foundation
  • High-impact role influencing product, platform, and GTM strategy
  • Small, high-caliber team solving meaningful problems in healthcare
  • Competitive compensation and meaningful equity
  • Opportunity to shape and grow the data function over time

Who we are

SuperDial is transforming AI in healthcare by building scalable, AI-powered solutions that optimize revenue cycle management. Join us and help shape the future of AI in healthcare!

The base salary for this role ranges from $185,000-$240,000, depending on experience, skill set, and fit. We also offer equity and benefits as part of our total compensation package. Final offers may vary based on experience and qualifications - we’re always open to exceptional talent.

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