Staff Software Engineer, Big Data, tvScientific
Pinterest · San Francisco, CA, US; Remote, US · Posted Jul 7, 2026
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About Pinterest:
Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.
Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible.
At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI.
Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here .
About tvScientific
tvScientific is the first and only CTV advertising platform purpose-built for performance marketers. We leverage massive data and cutting-edge science to automate and optimize TV advertising to drive business outcomes. Our solution combines media buying, optimization, measurement, and attribution in one, efficient platform. Our platform is built by industry leaders with a long history in programmatic advertising, digital media, and ad verification who have now purpose-built a CTV performance platform advertisers can trust to grow their business.
We are seeking a Staff Data Engineer to lead the design, implementation, and evolution of our identity services and data governance platform. This role is critical to ensuring trusted, privacy-safe, and well-governed data across the organization. You will work at the intersection of data engineering, identity resolution, privacy, and platform reliability. This is an individual contributor role, where you will work to define and implement a strategic vision for data engineering within the organization.
What you'll do:
Design and maintain a scalable identity resolution platform
Build pipelines and services to ingest, normalize, link, and version identity data across multiple sources
Ensure deterministic and probabilistic matching logic that is transparent, auditable, and measurable
Partner with product and analytics teams to expose identity data through reliable, well-documented APIs and datasets
Build and operate batch and streaming pipelines using modern data stack tools
Create clear documentation, standards, and runbooks for identity and governance systems
Own data governance foundations including data lineage, quality checks, schema enforcement, and access controls
Implement privacy-by-design principles (PII handling, consent enforcement, retention policies)
Collaborate with legal, privacy, and security teams to operationalize regulatory requirements (e.g., GDPR, CCPA)
Establish monitoring and alerting for data quality, freshness, and integrity
What we're looking for:
Production data engineering experience
Bachelor’s degree in computer science, related field or equivalent experience
Proficiency in Spark and Scala, with proven experience building data infrastructure in Spark using Scala
Experience in delivering significant technical initiatives and building reliable, large scale services
Experience in delivering APIs backed by relationship-heavy datasets
Experience implementing data governance practices, including data quality, metadata management, and access controls
Strong understanding of privacy-by-design principles and handling of sensitive or regulated data
Familiarity with data lakes, cloud warehouses, and storage formats
Strong proficiency in AWS services
Excellent written and verbal communication skills
Successful design and implementation of scalable and efficient data infrastructure
High attention to detail in implementation of automated data quality checks
Effective collaboration with cross-functional teams
Demonstrated ability to use AI to improve speed and quality in your day-to-day workflow for relevant outputs
Strong track record of critical evaluation and verification of AI-assisted work (e.g., testing, source-checking, data validation, peer review)
High integrity and ownership: you protect sensitive data, avoid over-reliance on AI, and remain accountable for final decisions and deliverables
In-Office Requirement Statement:
We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role.
Relocation Statement:
This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.
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