Data Engineering Lead

SuperDial

1d • $185,000 - $240,000

About The Position

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.

Requirements

• 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

Nice To Haves

• Experience working with high-performance or specialized data systems (e.g., ClickHouse or similar) is a plus

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

Benefits

• Competitive compensation and meaningful equity
• Opportunity to shape and grow the data function over time

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed
• Number of Employees: 11-50 employees