In this role, you will
- Architect complex, high-volume data pipelines for production use.
- Design and implement scalable data models serving multiple product and internal teams.
- Own data quality frameworks and standards across key data products.
- Build reusable patterns for transformations and metrics to drive efficiency.
- Define and maintain core business metrics and Key Performance Indicators (KPIs) in partnership with Analytics.
- Own the data products used across the company, ensuring reliability and performance.
- Set and promote standards for data modeling and pipeline development.
- Partner closely with Analytics, Data Science, and Machine Learning teams on requirements to reduce friction and accelerate their work.
- Mentor engineers and actively participate in the hiring process.
Qualifications
- 5+ years of experience in data engineering with a proven track record of successful data product development and oversight.
- Expert SQL and strong Python programming skills.
- Deep expertise in dbt or similar transformation frameworks.
- Strong data modeling experience across dimensional, activity schema, and similar patterns.
- Hands-on experience with data quality frameworks and performance tuning of data processes.
- Experience implementing both batch and streaming data processing patterns.
- Strong product thinking and stakeholder management skills.
- Excellent communication and collaboration skills to work effectively across teams.