\n 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. \n$180,000 - $220,000 a year \n