Staff Data Engineer

Job not on LinkedIn

🕒 April 20

🏄 California – Remote

🏄 California – Remote

💵 $177.2k - $364.8k / year

⏰ Full Time

🔴 Lead

🚰 Data Engineer

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Pinterest

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2010

📱 Media

👥 B2C

💰 Post IPO equity on 2022-08

Media • B2C

Pinterest is a visual discovery and bookmarking platform that helps users discover, save, and organize images and ideas (Pins) for interests, projects, and shopping. It provides personalized recommendations and visual search so people can plan and explore topics like home design, fashion, recipes, and events, and it supports commerce features and ads for creators and retailers.

📋 Description

• Design and maintain a scalable identity resolution platform • Build pipelines and services to ingest, normalize, link, and version identity data across multiple sources • Ensure deterministic and probabilistic matching logic that is transparent, auditable, and measurable • Partner with product and analytics teams to expose identity data through reliable, well-documented APIs and datasets • Build and operate batch and streaming pipelines using modern data stack tools • Create clear documentation, standards, and runbooks for identity and governance systems • Own data governance foundations including data lineage, quality checks, schema enforcement, and access controls • Implement privacy-by-design principles (PII handling, consent enforcement, retention policies) • Collaborate with legal, privacy, and security teams to operationalize regulatory requirements (e.g., GDPR, CCPA) • Establish monitoring and alerting for data quality, freshness, and integrity

🎯 Requirements

• Production data engineering experience • Bachelor’s degree in computer science, related field or equivalent experience • Proficiency in Spark and Scala, with proven experience building data infrastructure in Spark using Scala • Experience in delivering significant technical initiatives and building reliable, large scale services • Experience in delivering APIs backed by relationship-heavy datasets • 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 lakes, cloud warehouses, and storage formats • Strong proficiency in AWS services • Excellent written and verbal communication skills • Successful design and implementation of scalable and efficient data infrastructure • High attention to detail in implementation of automated data quality checks • Effective collaboration with cross-functional teams • 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

🏖️ Benefits

• Health insurance • Equity opportunities • Flexible work arrangements • Professional development