Consultant driving IA business growth in Deloitte's Artificial Intelligence & Data team. Delivering innovative solutions using data analytics and automation technologies.
About the role
- Data Engineering Lead overseeing data warehouse, pipelines, and analytics workflows at SuperDial. Driving data strategy and execution for impactful healthcare solutions.
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
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.)
- 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.
Benefits
- Competitive compensation and meaningful equity
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