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Sr. Software Engineer, Big Data, tvScientific
engineeringfull-timeSan Francisco, CA, US; Remote, US
SALARY
Not listed
WORK TYPE
remote
JOB TYPE
full-time
INDUSTRY
general
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About the role
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.
What you'll do:
- 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
- Collaborate closely with our Data Science and Product teams
How we'll define success:
- Successful 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 we're looking for:
- 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
- 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
- Strong track record of critical evaluation and verification of AI-assisted work
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