Contract Data Platform Engineer Jobs in Mena, AR

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).

Responsibilities:

• 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

Qualifications:

• 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

The base pay range for this position is $165K - $215K USD/year, which can include additional bonus depending on the position ultimately offered, in addition to a full range of medical, financial, and/or other benefits. The base pay offered may vary depending on job-related knowledge, skills, and experience.