Software Engineer (Big Data, tvScientific)

Role overview

Join tvScientific (part of Pinterest) as a Data Engineer / Software Engineer (Big Data). You’ll build and evolve robust data infrastructure and pipelines for performance advertising use cases, collaborating with cross-functional teams to deliver scalable data services and APIs.

Key missions

• Design and implement robust data infrastructure on AWS using Spark + Scala.
• Evolve core data pipelines for scalability and improved reliability.
• Collaborate cross-functionally to design data solutions aligned with business needs.
• Implement knowledge graphs.
• Leverage and optimize AWS resources while ensuring timely delivery of data assets and APIs.

Responsibilities

• Build and optimize production-grade data pipelines and services.
• Ensure data quality, validation, and verification throughout the workflow.
• Deliver APIs backed by relationship-heavy datasets.
• Apply data governance practices (quality, metadata management, access controls).
• Work with Data Science teams on machine learning pipelines.

Requirements

• Strong proficiency with AWS services.
• Expertise in SQL for data manipulation and extraction.
• Spark and Scala experience (building data infrastructure in Spark with Scala preferred).
• Familiarity with data lakes, cloud warehouses, and common storage formats.
• Experience delivering production data engineering initiatives and large-scale reliable services.
• Strong communication skills.
• High integrity and ownership: protect sensitive data, avoid over-reliance on AI, and remain accountable for final decisions.
• Ability to critically evaluate and verify AI-assisted work (testing, source-checking, data validation, peer review).

Nice-to-haves

• Experience in adtech.
• Experience with data governance and privacy-by-design for sensitive/regulated data.
• Familiarity with table formats such as Apache Iceberg and Delta.
• Experience implementing Data Engineering function.
• Experience delivering APIs for relationship-heavy datasets.
• Prior work with Data Science teams for ML pipelines.
• Demonstrated use of AI to improve speed and quality of daily workflow outputs.

Location / work model

• Full remote