Posted at: 28 January

Staff Data Engineer

Company

CompanytvScientific

tvScientific is a performance advertising platform for connected TV (CTV) based in the US, specializing in B2B ad tech solutions for performance marketers in consumer brands, gaming, and retail.

Remote Hiring Policy:

tvScientific embraces a remote-first work environment, allowing employees to work from most locations in the US. While specific roles may have unique requirements, the company supports flexibility in remote work arrangements.

Job Type

Full-time

Allowed Applicant Locations

United States

Salary

$120,000 to $160,000 per year

Job Description

Job Title: Staff Data Engineer
Location: Remote, US
Department: Engineering
Type: Full-Time, Exempt
Experience: 8+ years of experience
Core Hours: 9 AM - 1 PM PST

 

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 the Staff 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. 

 

Your expertise in Spark and Scala (5 years minimum) will be critical for success.

 

What You'll 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 We'll 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

 

You’ll Be Successful in This Role if You Have

  • Minimum of 8 years of full-time experience in data engineering
  • Proven experience building data infrastructure using Spark with Scala for at least 5 years
  • 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
  • Bachelor's degree in Computer Science or a related field

 

Bonus Points if You Also Have

  • 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

 

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.