Software Engineer II, Data Analytics & Engineering

About Pinterest:

Millions of people around the world come to our platform to find creative ideas dream about new possibilities and plan for memories that will last a lifetime. At Pinterest were on a mission to bring everyone the inspiration to create a life they love and that starts with the people behind the product.

Discover a career where you ignite innovation for millions transform passion into growth opportunities celebrate each others unique experiences and embrace theflexibility to do your best work. Creating a career you love Its Possible.

At Pinterest AI isnt just a feature its a powerful partner that augments our creativity and amplifies our impact and were looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities well explore your foundational skills and how you collaborate with AI.

Through our interview process what matters most is that you can always explain your approach showing us not just what you know but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here.

Job Title: Software Engineer II Data Analytics and Engineering

Intro: Were 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. Youll 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 youll 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 were 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.
• Bachelors 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 12 times per month and therefore can be situated anywhere in the country.

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