Senior Principal Data Engineer

About Cardlytics

Founded in 2008, Cardlytics (NASDAQ: CDLX) is the industry-leading purchase intelligence and incentives platform. We make commerce smarter and more rewarding for everyone by helping businesses attract, understand, and incentivize consumers through our partners' digital reward programs. Join us on our mission to make commerce smarter and more rewarding for everyone!

The Ads Marketplace team at Cardlytics comprises a dynamic group of scientists and engineers dedicated to rethinking and redefining ad delivery and optimization  work directly impacts millions of customers daily, driving innovation and effectiveness in how advertising reaches its audience. We are undergoing a strategic shift to unify our data engineering, experiment tracking, and model deployment within a robust Databricks-native ecosystem to accelerate time-to-market and enhance platform stability.

As a Senior Principal Data Engineer, you will serve as the primary architect and strategic lead for our MLOps and forecasting platform. You will bridge the gap between advanced data science and production-grade engineering, ensuring that complex models for campaign projections, lift analysis, and budget forecasting are scalable, high-performance production services. You will lead the design of our data infrastructure, overseeing the implementation of automated pipelines using the Databricks Data Intelligence Platform (including Databricks SQL, Unity Catalog, and MLflow) to enable precise, real-time data consumption and model deployment.

Design and architect a unified MLOps and forecasting platform on Databricks, leveraging MLflow for model orchestration and Databricks SQL for high-scale data processing. Build and maintain automated pipelines to handle critical business use cases, specifically:

• Developing models that simulate past campaign performance using historical transaction data to forecast future outcomes.
• Real-time monitoring and prediction of budget utilization to prevent over/under delivery.
• Implementing robust Incrementality Testing framework to quantify the causal impact of advertising exposure.
• Establish CI/CD and deployment standards to ensure models are scalable, frequently refreshed, and easily debugged.
• Define "clean data" and telemetry-first standards.
• Analyze large datasets to identify trends and insights that improve model performance and advertising outcomes.
• Partner with Applied Scientists to explore GenAI patterns and automated architectures to enhance team workflows.
• Collaborate with product and business stakeholders to translate high-level business goals into technical roadmaps that prioritize explainable, scalable, and accurate engineering solutions.
• Act as a technical mentor for senior and staff engineers, fostering a culture of operational excellence and rapid dev velocity.

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field;
  PhD preferred.
• 10+ years of experience in data engineering, with a significant focus on building and scaling MLOps pipelines in a production environment.
• Expertise in the Databricks Data Intelligence Platform, including Unity Catalog and MLflow, for big data and ML workloads.
• Proficiency in Python, SQL, and PySpark, with deep knowledge of data modeling and semantic layer design for large-scale analytics.
• A proven track record of leading large-scale architectural migrations and managing technical debt.
• Strong understanding of time-series forecasting, statistical modeling, or causal inference (e.g., Lift Analysis).
• Exceptional communication skills, with the ability to influence executive stakeholders and align technical strategy with business goals.

• Expertise in integrating complex prediction models (ranking, retrieval, and conversion) into high-traffic Marketplace funnels.
• Experience with real-time systems and large-scale data processing technologies (e.g., Kafka, Kinesis).
• Familiarity with Learning to Rank (LTR) models and their productionization challenges.
• Demonstrated ability to implement AI-powered assistants for product development, alert triage, and workload migration.