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Sr. Data Engineer, tvScientific

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At a Glance

Location
San Francisco, CA, US; Remote, US
Work Regime
remote
Department
tvScientific
Posted
2026-02-25T14:55:38-05:00

Key Requirements

Required Skills

AWSData EngineeringSQLScala

Domain Knowledge

  • Engineering

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

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

About the Company

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.