Pinterest

Software Engineer II, Data Analytics & Engineering

Pinterest$123K — $254K *
US-AnywhereRemote in San Francisco, CA
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Minimum 2 years of experience in analytics engineering or data solutions within a fast-paced environment.
  • Proficient in SQL and Python, R or a similar language for handling large datasets.
  • Experience with data workflows, ETL/ELT pipelines, and complex dataset management.
  • Ability to effectively translate partner needs into technical objectives across teams.
  • Demonstrated skill in leveraging AI to enhance engineering processes.
  • Proven track record of validating and critiquing AI-assisted output.
  • Bachelor's degree in Computer Science, Statistics, Mathematics, or similar field, or equivalent experience.

Responsibilities

  • Develop and document standards for practical instrumentation and experimentation.
  • Build and enhance scalable analysis pipelines and tools for reliable insights.
  • Create processes for Data Scientists and Engineers to access trusted datasets independently.
  • Identify and advocate for improvements in data quality and discoverability.
  • Maintain clear documentation for tools, datasets, metrics, and practices.
  • Collaborate with cross-functional teams to communicate actionable insights.
  • Utilize AI to expedite analysis and ensure quality and responsible application.

Benefits

  • Flexible work model with occasional in-office collaboration requirement.
  • Focus on equitable and inspiring workplace culture.
  • Eligibility for equity in addition to compensation.
Full Job Description
Job Title: Software Engineer II, Data Analytics and Engineering

Intro: We're looking for a Software Engineer II, Data Analytics and Engineering to improve the quality, reliability and velocity of data science and product development at Pinterest. You'll build scalable data foundations, analytics tooling and analysis pipelines that enable trusted, self-service access to datasets, insights and metric investigations across cross-functional teams.

What you'll do:
  • Develop and document practical instrumentation and experimentation standards, then partner with product engineering teams to apply them to priority product development work.
  • Build and improve scalable analysis pipelines and tooling that produce reliable insights at scale and strengthen understanding of key data structures and metrics.
  • Create tools and processes that enable Data Scientists and Engineers to independently access trusted datasets, insights and metric definitions.
  • Identify data quality and discoverability gaps, advocate for targeted improvements and contribute to reliable, well-governed data practices.
  • Maintain clear documentation for tools, datasets, metrics and operating practices to make team data assets easier to use.
  • Partner with Product, Engineering, Data Science, Data Engineering and Business Intelligence teams to communicate actionable insights and inform product improvements.
  • Use AI to accelerate analysis, prototyping and iteration, while applying judgment and verification to ensure correctness, quality and responsible use.

What we're looking for:
  • Minimum of 2 years of experience delivering analytics engineering or data solutions in a fast-paced, data-driven environment.
  • Experience using SQL and Python, R or a comparable programming language to work with large, high-dimensional datasets, including nested data structures, window functions, query optimization and data partitioning.
  • Experience building and operating data workflows, including workflow orchestration, ETL/ELT pipelines and DAG dependencies across complex datasets.
  • Experience translating open-ended partner needs into clear, impactful technical objectives and collaborating across Product, Engineering, Data Science, Data Engineering and Business Intelligence teams.
  • Demonstrated ability to use AI to improve speed and quality in day-to-day engineering workflows.
  • Strong track record of critically evaluating and verifying AI-assisted work through testing, data validation, source-checking or peer review.
  • High integrity and ownership: you protect sensitive data, avoid over-reliance on AI and remain accountable for final decisions and deliverables.
  • Bachelor's degree in a relevant field such as Computer Science, Statistics, Mathematics or a related discipline, or equivalent experience.

Relocation Statement:
  • This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

In-Office Requirement Statement:
  • We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role.
  • This role will need to be in the office for in-person collaboration 1-2 times per month and therefore can be situated anywhere in the country.


#LI-REMOTE

#LI-AG8

At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.

Information regarding the culture at Pinterest and benefits available for this position can be found here.

US based applicants only

$123,696-$254,667 USD

About Pinterest

Pinterest is a social media platform that allows users to discover and save ideas for recipes, home decor, fashion, and more. The company was founded in 2010 and is headquartered in San Francisco, California. Pinterest has over 400 million monthly active users and is available in over 30 languages. The company's mission is to help people discover and do what they love.
Learn more about Pinterest
Size
3,225 employees
Market Cap
$16 billion
Industry
Net Income
-$128.3 million
Founded
2009
5 Year Trend
+53.9%
Revenue
$1.6 billion
NASDAQ

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