Software Engineer II, Big Data

Vaga não está no LinkedIn

🕒 Maio 28

🏄 California – Remoto

🏄 California – Remote

💵 $123.696 - $254.667 / ano

⏰ Tempo Integral

🟡 Pleno

🟠 Sênior

🧑‍💻 Engenheiro Full-stack

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tvScientific

SiteLinkedInTodas as Vagas

51 - 200 funcionários

Fundada em 2020

📱 Mídia

☁️ SaaS

🤝 B2B

Media • SaaS • B2B

tvScientific é uma plataforma de publicidade em TV Conectada (CTV) focada em performance que utiliza otimização baseada em IA para fornecer resultados de negócios mensuráveis, como instalações, vendas e tráfego. A plataforma oferece acesso a inventário, segmentação, gerenciamento criativo, mensuração e atribuição, além de relatórios em tempo real com um painel unificado e análises transparentes. A tvScientific se posiciona como uma solução paga por performance para marcas de consumo, oferecendo resultados garantidos, controles de segurança de marca e integrações para escala.

Descrição

• 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

🎯 Requisitos

• 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 • 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. • Experience in adtech (nice-to-have) • Experience implementing data governance practices, including data quality, metadata management, and access controls (nice-to-have) • Strong understanding of privacy-by-design principles and handling of sensitive or regulated data (nice-to-have) • Familiarity with data table formats like Apache Iceberg, Delta (nice-to-have) • Previous experience building out a Data Engineering function (nice-to-have) • Proven experience working closely with Data Science teams on machine learning pipelines (nice-to-have)

🏖️ Benefícios

• Health insurance • Stock options • Professional development opportunities