Senior Principal Data Engineer: MLOps & Forecasting

Cardlytics; Northern (KY); Hybrid; USD 150,000 - 200,000; Full time

Benefits offered by this job

Flexible paid time off

Medical, dental, and vision insurance

401(k) retirement plan with company 13

Employee Stock Purchase Plan

Educational assistance

Wellbeing stipend

Calm app subscriptions

Job summary

Cardlytics seeks a Senior Principal Data Engineer to architect a unified MLOps and forecasting platform on Databricks. You will bridge advanced data science with production-grade engineering, ensuring scalable models for campaign projections and budget forecasting.

Lead automated pipelines, oversee model deployment using MLflow, and collaborate with product teams to translate business goals into technical roadmaps. Strong leadership and communication skills required.

Qualifications

• Bachelor’s or Master’s degree in Computer Science/Engineering or related field; PhD preferred.
• 10+ years of data engineering experience with pipelines in production.
• Expertise with Databricks Data Intelligence Platform (Unity Catalog, MLflow).
• Proficiency in Python, SQL, and PySpark for large-scale analytics.

Responsibilities

• Design and architect a unified MLOps and forecasting platform on Databricks.
• Build and maintain automated pipelines for campaign projections, lift analysis, and budget forecasting.
• Lead model orchestration and high-scale data processing with Databricks SQL and MLflow.
• Mentor senior engineers and align technical work with business goals.

Skills

Python

SQL

PySpark

MLOps

Databricks

MLflow

Data modeling

Semantic layer design

Time-series forecasting

Causal inference

Education

Bachelor’s or Master’s in Computer Science/Engineering; PhD preferred

Tools

Databricks Unity Catalog

Databricks SQL

MLflow

Job description

Cardlytics seeks a Senior Principal Data Engineer to architect a unified MLOps and forecasting platform on Databricks. You will bridge advanced data science with production-grade engineering, ensuring scalable models for campaign projections and budget forecasting.

Lead automated pipelines, oversee model deployment using MLflow, and collaborate with product teams to translate business goals into technical roadmaps. Strong leadership and communication skills required.