Software Engineer II, Big Data, tvScientific

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

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

Production data engineering experience

Proficiency in Spark and Scala, with proven experience building data infrastructure in Spark using Scala is preferred

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

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 (e.g., testing, source-checking, data validation, peer review)

High integrity and ownership: you protect sensitive data, avoid over-reliance on AI, and remain accountable for final decisions and deliverables

Nice-to-haves: 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

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