Software Engineer II, Big Data, tvScientific

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 were 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 others unique experiences and embrace theflexibility to do your best work. Creating a career you love Its Possible.

At Pinterest AI isnt just a feature its a powerful partner that augments our creativity and amplifies our impact and were looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities well 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 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 youll 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 well 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 were looking for:

• 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
• Bachelors 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

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 ourPinFlexpage to learn more about our working model.

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