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.
As a Staff Data Engineer at tvScientific, you will be a key player in implementing the robust data infrastructure to power our data-heavy company. You will collaborate with our cross-functional teams to evolve our core data pipelines, design for efficiency as we scale, and store data in optimal engines and formats. 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 implement robust data infrastructure in AWS, using Spark with Scala
- Evolve our core data pipelines to efficiently scale for our massive growth
- Store data in optimal engines and formats, matching your designs to our performance needs and cost factors
- Collaborate with our cross-functional teams to design data solutions that meet business needs
- Design and implement knowledge graphs, exposing their functionality both via Batch Processing and APIs
- Leverage and optimize AWS resources while designing for scale
- Collaborate closely with our Data Science and Product teams
- How we'll define success:
- Successful design and implementation of scalable and efficient data infrastructure
- Timely delivery and optimization of data assets and APIs
- High attention to detail in implementation of automated data quality checks
- Effective collaboration with cross-functional teams
What we're looking for:
- Production data engineering 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
- Familiarity with data lakes, cloud warehouses, and storage formats
- Strong proficiency in AWS services
- Expertise in SQL for data manipulation and extraction
- Excellent written and verbal communication skills
- Bachelor's degree in Computer Science or a related field
- Nice-to-haves:
- Experience in adtech
- 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 table formats like Apache Iceberg, Delta
- Previous experience building out a Data Engineering function
- Proven experience working closely with Data Science teams on machine learning pipelines
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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At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.
Information regarding the culture at Pinterest and benefits available for this position can be found here.
Our Commitment to Inclusion: