Software Engineer Ii, Data

Pinterest Pinterest · Consumer · Toronto, ON · Data Engineering

Software Engineer II, Data at Pinterest. This role focuses on data engineering, designing and maintaining data pipelines, and creating data products. The role explicitly mentions leveraging AI tools for productivity, such as drafting, prototyping, summarizing, and automating tasks. It also requires experience with LLMs and AI agents for productivity, and a strong track record of evaluating AI-assisted work. The primary focus is on data engineering (L0), with AI being a tool for productivity rather than the core deliverable.

What you'd actually do

  1. Understand the business drivers and analytical use-cases and translate these to data products.
  2. Design, implement and maintain pipelines that produce business critical data reliably and efficiently using cloud technology.
  3. Leverage AI to seek faster execution (i.e. draft, prototype, outline) and explore alternative options (i.e. iterate, compare approaches)
  4. Leverage AI to synthesize information (summarize, distill themes) and automate repeatable tasks (documentation, reporting, QA checks)
  5. Collaborate with many teams from Product, Engineering and Business to produce relevant data solutions that can be used across multiple use cases.

Skills

Required

  • 2+ years of experience with big data (Hive, Iceberg, Presto, Spark, SparkSQL, Scala, Airflow)
  • scripting language (Python)
  • principled data warehouse design
  • data pipeline design and development
  • data visualization
  • Experience using large language models and developing AI agents to boost productivity
  • Great communication skills
  • Experience in working independently and driving projects end to end
  • Strong analytical skills
  • 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
  • High integrity and ownership
  • Bachelor’s or Master’s degree in a relevant field such as Data Engineering, or equivalent experience

Nice to have

  • Data visualization technologies (Tableau, Looker, Superset)

What the JD emphasized

  • Experience using large language models and developing AI agents to boost productivity
  • 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.

Other signals

  • Leverage AI to seek faster execution
  • Leverage AI to synthesize information
  • Experience using large language models and developing AI agents to boost productivity
  • Demonstrated ability to use AI to improve speed and quality in your day-to-day workflow
  • Strong track record of critical evaluation and verification of AI-assisted work