Staff Software, Engineering – Analytics Engineering, Core Data Science
About this role
Pinterest builds a visual search and discovery platform that brings inspiration to millions of people globally, relying heavily on artificial intelligence as a core partner for product experiences. The Core Data Science analytics engineering team creates robust data foundations, internal tooling, and scalable analysis pipelines to improve data science velocity and product quality. This staff engineer guides a high-performing group, collaborates across functions with product managers and researchers, and shapes business-facing features through advanced data practices.
Candidates joining this team will build and prototype AI-driven tools, establish best practices for experimentation, and drive data democratization across the organization. The ideal person brings substantial technical depth in handling complex datasets, leverages modern AI workflows with strict verification standards, and demonstrates strong mentorship capabilities. Someone who thrives in a collaborative environment and can independently translate ambiguous objectives into structured, impactful engineering outcomes will succeed in this role.
What you will do
- Lead by example and mentor a diverse team of analytics engineers while fostering an inclusive culture.
- Develop and communicate best practices for instrumentation and experimentation to product engineering teams.
- Build and prototype AI tools and analysis pipelines iteratively to deliver scalable insights and robust data foundations.
- Utilize AI to accelerate analysis, prototyping, and iteration while applying rigorous judgment and verification to ensure correctness.
- Partner closely with data scientists and engineers to construct tools and processes enabling self-service of key datasets.
- Contribute to comprehensive documentation and drive strategies for data quality and democratization across Pinterest.
- Collaborate cross-functionally with product managers, engineers, designers, and researchers to shape upcoming user experiences.
What you need
- Minimum of 6 years of experience working with data in a fast-paced, data-driven environment.
- High fluency in SQL or other database languages alongside Python or R for manipulating large, complex datasets.
- Demonstrated experience conducting workflow orchestration and ETL/ELT operations with large datasets and DAG dependencies.
- Track record of taking open-ended goals, scoping them into defined objectives, and delivering actionable analytics solutions.
- Demonstrated ability to use AI for workflow acceleration combined with critical evaluation and validation of AI-assisted outputs.
- Bachelor's, Master's, or PhD in Computer Science, Statistics, Mathematics, or a related quantitative field, or equivalent experience.
Nice to have
- Experience in automation, anomaly detection, or infrastructure and workflow optimization
- Experience building internal tooling to maximize engineering velocity
Benefits
- Eligible for equity
Skills and tech stack
Questions candidates ask
What is the remote work policy for this position?
The role utilizes a flexible working model called PinFlex and can be situated anywhere in the country. However, the position requires being in the office for in-person collaboration 1-2 times per month.
What is the compensation range for this role?
The base salary range for this position is $177,185 to $364,795 USD per year. The position is also eligible for equity, with the final salary determined by factors such as location, travel, relevant prior experience, and particular skills.
What technologies and tools will I be using?
The position requires fluency in SQL or other database languages, as well as a scripting language like Python or R. Team members also use AI tools to accelerate analysis, prototyping, and iteration.
What does the interview process evaluate?
The evaluation explores foundational skills and how candidates collaborate with AI. Throughout the process, what matters most is that applicants can explain their approach to show both what they know and how they think.