Sr. Software Engineer, Big Data, Tvscientific

Pinterest Pinterest · Consumer · San Francisco, CA · tvScientific

Senior Data Engineer role focused on building and scaling robust data infrastructure using AWS, Spark, and Scala. The role involves evolving core data pipelines, optimizing data storage, and collaborating with Data Science and Product teams to design data solutions. While the role emphasizes using AI tools to improve workflow and critically evaluating AI-assisted work, the core responsibility is data engineering, not direct AI/ML model development.

What you'd actually do

  1. Implement robust data infrastructure in AWS, using Spark with Scala
  2. Evolve our core data pipelines to efficiently scale for our massive growth
  3. Store data in optimal engines and formats
  4. Collaborate with our cross-functional teams to design data solutions that meet business needs
  5. Built out fault-tolerant batch and streaming pipelines

Skills

Required

  • Production data engineering experience
  • Proficiency in Spark and Scala
  • Familiarity with data lakes, cloud warehouses, and storage formats
  • Strong proficiency in AWS services
  • Expertise in SQL
  • 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 have

  • 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

What the JD emphasized

  • Production data engineering experience
  • Proficiency in Spark and Scala, with proven experience building data infrastructure in Spark using Scala
  • Strong proficiency in AWS services
  • 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