Principal Data Engineer

Job summary

Goo*** is the leading prescription savings platform in the U. Trusted by more than 25 million consumers and 750,000 healthcare professionals annually, Goo*** provides access to savings and affordability options for generic and brand-name medications at more than 70,000 pharmacies nationwide, as well as comprehensive healthcare research and information.

Benefits

Qualifications

• AI is a core part of how we operate, and as a Principal Data Engineer you are expected to help define how AI is applied responsibly across our data platform and engineering practices.
• 10+ years of experience in data engineering, including demonstrated experience defining technical strategy and influencing engineering organizations beyond a single team.
• Experience with one of the cloud environments - AWS, GCP.
• Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets.
• Experience designing, building, and evolving enterprise-scale data platforms that support multiple engineering teams, analytics, and machine learning workloads.
• Ability to quickly learn complex domains and new
• and other relevant business and organizational factors.
• These pay zones may be modified in the future.
• Please contact your recruiter for additional information.
• San Francisco and Seattle Offices:
• 226,000.00 - $361,000.00
• New York Office:

Responsibilities

• Define the long-term technical vision and architecture for the Data Platform, partnering with Product, Engineering, Data Science, and Analytics leaders to align platform investments with business strategy.
• Provide technical leadership and mentorship across multiple engineering teams, influencing architectural decisions, raising engineering standards, and developing future technical leaders.
• Lead the architectural evolution of the data platform to improve scalability, reliability, operational efficiency, and long-term maintainability.
• Drive investments in developer experience, platform tooling, CI/CD automation, observability, and self-service capabilities that improve engineering productivity and platform reliability.
• Develop architectural proposals, technical standards, and engineering design documentation that guide long-term platform strategy and evolution.
• Lead complex platform modernization initiatives, large-scale migrations, and architectural transformations with minimal disruption to the business.
• Establish organization-wide standards for data architecture, engineering quality, platform governance, and reusable engineering patterns.
• Drive long-term engineering and platform strategy through data-informed decision-making, balancing scalability, reliability, cost efficiency, and developer productivity.
• Lead enterprise-scale platform initiatives that enable analytics, machine learning, AI workloads, and scalable product development across Goo***.

Skills

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