Senior Data Engineer, AI Systems

Movable Ink is a company that scales content personalization for marketers through data-activated content generation and AI decisioning. As a Senior Data Engineer, you will own the Spark-based data pipelines and data infrastructure that powers AI-driven marketing decisions, working collaboratively with ML engineers and scientists to optimize the data layer for production ML models.

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

Requirements:

• 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