About the job
As the Data Engineering Lead at SuperDial, you will take full ownership of our data platform, overseeing everything from data warehousing to analytics workflows. This role is crucial in scaling our data infrastructure and ensuring that data-driven insights effectively guide product decisions, market strategies, and overall company planning.
We are seeking a candidate with a robust background in analytics engineering, who is eager to transition into a leadership role. You will utilize your analytical expertise to proactively influence the strategic direction of SuperDial.
Key Responsibilities:
Lead the scaling of SuperDial’s data warehouse and analytics stack.
Develop and maintain robust dbt transformation layers to ensure trusted metrics.
Design and manage data pipelines that integrate product, go-to-market, and platform data.
Oversee data engineering workflows, orchestration, and dependencies.
Collaborate with product and platform teams to meet operational and analytical data requirements.
Create and maintain clean, well-documented data models that serve as the business's source of truth.
Develop impactful dashboards and analyses to inform on revenue, product usage, and customer behavior.
Implement data quality checks and monitoring to ensure reliable, decision-ready data.
Establish best practices for modeling, testing, and analytics development as the company scales.
30/60/90 Day Expectations:
First 30 Days:
Familiarize yourself with SuperDial’s product offerings, data sources, and existing data warehouse.
Conduct an audit of current dbt models, pipelines, orchestration, and reporting.
Assess platform data needs and performance considerations.
Deliver initial improvements to data quality, reliability, or documentation.
Build relationships with Product, Platform, GTM, and Finance teams.
Next 60 Days:
Assume complete ownership of the data warehouse and analytics processes.
Refactor core dbt models to ensure consistent metrics.
Enhance orchestration, testing, and monitoring across all data pipelines.
Collaborate with engineering teams on platform-oriented data solutions.
