Staff Data Engineer

Sorry, this job was removed Sorry, this job was removed at 06:07 p.m. (CST) on Saturday, Apr 19, 2025
Hiring Remotely in USA
Remote
AdTech • Marketing Tech
The Role

Job Title: Staff Data Engineer
Location: Remote, US
Department: Engineering
Type: Full-Time, Exempt
Experience: 8+ years of experience
Salary Range: $185,000 - $200,000 (based on experience)
Core Hours: 9 AM - 1 PM PST / 12 - 4 PM EST


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.


Role Summary

As a Staff Data Engineer at tvScientific, you will be a key player in designing and implementing the robust data infrastructure to power our data-heavy company. You will collaborate with our cross-functional teams to build out our core data pipelines, store data in optimal engines and formats, and feed our machine learning models.

This is an individual contributor role with the potential to lead, where you will work closely with our VP of Technology to define and implement a strategic vision for data engineering within the organization. Your expertise in Spark and Scala will be critical for success.


What You'll Do

  • Design and implement robust data infrastructure using Spark with Scala.
  • Collaborate with our cross-functional teams to design data solutions that meet business needs.
  • Build out our core data pipelines, store data in optimal engines and formats, and feed our machine learning models.
  • Leverage and optimize AWS resources.
  • Collaborate closely with the Data Science team.


How We'll Define Success

  • Successful design and implementation of scalable and efficient data infrastructure.
  • Timely delivery and optimization of ETL processes.
  • Effective collaboration with cross-functional teams.
  • Seamless integration with Data Science for machine learning pipelines.


You’ll Be Successful in This Role if You Have/Are

  • 8+ years of experience in data engineering.
  • Proven experience building data infrastructure using Spark with 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.


You May Also Have

  • Experience in adtech.
  • Familiarity with Elastic Map Reduce (EMR).
  • Previous experience leading and/or building out a Data Engineering function.
  • Proven experience working closely with Data Science teams on machine learning pipelines.


Culture and Benefits

At tvScientific we believe people do their best work when they feel challenged and engaged by their day to day responsibilities, when they’re surrounded by smart, hard working people, and when they have a healthy work life balance. Our company culture and benefits package reflects these beliefs.

  • Full health, dental, and vision insurance - up to 95% funded by the company for employees.
  • Employee stock option program.
  • Company-sponsored retirement plan with a matching contribution program.
  • 12 annual paid holidays (including 2 flexible days).
  • Generous PTO policy (get your work done and take the time you need).
  • A remote-first environment that allows employees flexibility to work from most places in the US.


As tvScientists We Are...

  • Big Thinkers: We believe in setting audacious goals and envisioning transformative change.
  • Radically Transparent: We value transparency in all aspects of our business. We foster a culture of open communication, honesty, and accountability.
  • Performance-obsessed: We are passionate about achieving exceptional results. We strive for excellence in everything we do and set high standards for ourselves.
  • Data-driven: We embrace the power of data, science, and technology as crucial drivers of our success.
  • Trust Builders: We prioritize building and nurturing trust with our stakeholders. We understand that trust is the foundation of successful relationships and business partnerships. Through our actions, integrity, and commitment to delivering on promises.
  • Forever Students: Challenge assumptions to look for solutions. We create a safe environment for experiments and risk-taking by our customers and employees.


tvScientific is committed to building an inclusive environment for people of all backgrounds and everyone is encouraged to apply. tvScientific is an Equal Opportunity Employer and does not discriminate on the basis of race, color, gender, sexual orientation, gender identity or expression, religion, disability, national origin, protected veteran status, age, or any other status protected by applicable national, federal, state, or local law.

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The Company
Los Angeles, , CA
137 Employees
On-site Workplace
Year Founded: 2020

What We Do

tvScientific is the first and only CTV advertising platform purpose built for serious performance marketers. The tvScientific platform makes TV advertising accessible and measurable for brands and apps of all sizes. tvScientific offers a self-managed solution that simplifies and automates TV buying and optimization, leveraging massive data to prove the actual value of TV advertising. The platform reaches 95% of AVOD inventory using proprietary, deterministic ID technology to measure ad exposure to outcome in an approachable, radically transparent and scalable way. An Idealab company, tvScientific was co-founded by senior executives with deep roots in programmatic advertising, digital media, and ad verification. The company is headquartered in Pasadena, California. For more information, visit https://www.tvscientific.com

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