Senior Data Engineer

Who you are

• 5+ years of data engineering experience
• Deep expertise with Apache Spark, including the PySpark DataFrame API and experience solving challenging scaling problems
• Experience with large-scale data processing, cluster configuration, optimization, and tuning (we use GCP Dataproc)
• Strong software development skills in Python (unit testing, git, code review, CI/CD)
• Experience with data storage formats (we use Parquet, Delta Lake)
• Experience with event streaming data (we use Kafka)
• Experience with cloud computing platforms (we use Google Cloud Platform)
• Experience with advanced query optimization
• Familiar with Software Development Lifecycle practices, such as continuous integration/continuous delivery and automated deployment (we use Docker, Kubernetes, and GitHub Actions)
• Ability to collaborate with technical partners - you'll be working closely with ML engineers, scientists, and other teams to determine requirements and make design decisions
• Enjoys working in a fast-paced, goal-driven environment
• If you’re excited about the role but don’t meet all of the abovementioned qualifications, we encourage you to apply. Our differences bring a breadth of knowledge and perspectives that makes us collectively stronger

What the job involves

• The AI Systems team owns the core recommendations engine and ML platform that powers billions of AI-driven marketing decisions daily across some of the world's largest consumer brands. As a Senior Data Engineer, you will own the Spark-based data pipelines and data infrastructure at the heart of this system - building, scaling, and optimizing the data layer that feeds our production ML models
• You will work alongside ML engineers and scientists in a collaborative environment, contributing data pipelines and products to power our core recommender systems and our DaVinci Personalization product. This is an opportunity to work end-to-end on large-scale data systems that touch millions of customers, on a team working at the intersection of data engineering and machine learning
• This role will be reporting to the Director of Engineering (AI/ML)
• Build, maintain, and optimize production data pipelines that power AI-driven personalization at scale across content selection, send-time optimization, subject line personalization, and frequency capping
• Own and scale Spark-based batch pipelines, including cluster configuration, tuning, and performance optimization across GCP Dataproc
• Build and maintain our ML Data Lake, ensuring data quality, accessibility, and efficient storage
• Support the data needs of ML Engineers and Scientists for model development, training, and evaluation
• Identify and resolve performance bottlenecks and scaling limitations in data pipelines and infrastructure
• Collaborate with distributed systems engineers on the platform's architectural evolution, ensuring data layer continuity throughout
• Continuously improve data infrastructure for greater scalability and reliability
• Release features and data products that deliver measurable and tangible business value

Benefits

• Generous PTO
• Global Mental Health and Well-Being Benefits
• Flexible Work Opportunities
• Comprehensive Health Benefits
• 401K Contribution
• Employee Resource Groups
• Parental Leave and Support
• Volunteer Opportunities
• Social Events and Activities