RemoteFull timeMid level$124k – $255kPosted today
Apply with JobAssistAbout the role
- 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
- 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- Strong proficiency in AWS services
- Expertise in SQL for data manipulation and extraction
- Bachelor’s 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
- Excellent written and verbal communication skills
- High integrity and ownership: you protect sensitive data, avoid over-reliance on AI, and remain accountable for final decisions and deliverables
- Proficiency in Spark and Scala, with proven experience building data infrastructure in Spark using Scala is preferred
- Familiarity with data lakes, cloud warehouses, and storage formats
- Experience in delivering APIs backed by relationship-heavy datasets
- Production data engineering experience
- Experience in delivering significant technical initiatives and building reliable, large scale services
- Strong track record of critical evaluation and verification of AI-assisted work (e.g., testing, source-checking, data validation, peer review)
- 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
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