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About PinterestMillions 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.About tvScientifictvScientific 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.As a 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 doDesign and implement robust data infrastructure in AWS, using Spark with ScalaEvolve our core data pipelines to efficiently scale for our massive growthStore data in optimal engines and formats, matching your designs to our performance needs and cost factorsCollaborate with our cross-functional teams to design data solutions that meet business needsDesign and implement knowledge graphs, exposing their functionality both via Batch Processing and APIsLeverage and optimize AWS resources while designing for scaleCollaborate closely with our Data Science and Product teamsHow we'll define success:Successful design and implementation of scalable and efficient data infrastructureTimely delivery and optimization of data assets and APIsHigh attention to detail in implementation of automated data quality checksEffective collaboration with cross-functional teamsWhat we're looking for:Production data engineering experienceProficiency in Spark and Scala, with proven experience building data infrastructure in Spark using Scala is preferredExperience in delivering significant technical initiatives and building reliable, large scale servicesExperience in delivering APIs backed by relationship-heavy datasetsFamiliarity with data lakes, cloud warehouses, and storage formatsStrong proficiency in AWS servicesExpertise in SQL for data manipulation and extractionExcellent written and verbal communication skillsBachelor's degree in Computer Science or a related fieldDemonstrated ability to use AI to improve speed and quality in your day-to-day workflow for relevant outputsStrong 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 deliverablesNice-to-haves:Experience in adtechExperience implementing data governance practices, including data quality, metadata management, and access controlsStrong understanding of privacy-by-design principles and handling of sensitive or regulated dataFamiliarity with data table formats like Apache Iceberg, DeltaPrevious experience building out a Data Engineering functionProven experience working closely with Data Science teams on machine learning pipelinesIn-Office Requirement StatementWe 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 StatementThis position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.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.US based applicants onlyOur Commitment to InclusionPinterest is an equal opportunity employer and makes employment decisions on the basis of merit.
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