About the company
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.
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.
Responsibilities
- 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.
Requirements
- Production data engineering experience.
- Proficiency in Spark and Scala, with proven experience building data infrastructure in Spark using Scala is preferred.
- 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.
- 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.
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.