Sr. Data Engineer, tvScientific

PinterestSan Francisco, CA
3h

About The Position

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 Senior 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.

Requirements

  • Production data engineering experience
  • Proficiency in Spark and Scala, with proven experience building data infrastructure in Spark using Scala
  • 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

Responsibilities

  • 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
  • Collaborate with our cross-functional teams to design data solutions that meet business needs
  • Built out fault-tolerant batch and streaming pipelines
  • Leverage and optimize AWS resources while designing for scale
  • Collaborate closely with our Data Science and Product teams
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