Senior Principal Data Engineer, MLOps & Forecasting

cardlytics; United States; On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Flexible paid time off

Insurance begins day one

401(k) with company match

Student loan debt support

Job summary

Cardlytics is seeking a Senior Principal Data Engineer (IC6) to lead the design and implementation of an enterprise-scale MLOps and forecasting platform built on the Databricks Data Intelligence Platform. You will bridge data science and production engineering, delivering scalable pipelines and real-time budget predictions.

The role emphasizes architecture leadership, telemetry-driven development, and close collaboration with Applied Scientists and business stakeholders to align technical work

Qualifications

• 10+ years of data engineering with a focus on MLOps pipelines in production.
• Expertise in Databricks Data Intelligence Platform, Unity Catalog and MLflow.
• Strong Python, SQL and PySpark skills; capable of large-scale analytics.
• Proven track record leading architectural migrations and managing technical debt.

Responsibilities

• Design and architect an integrated MLOps and forecasting platform on Databricks.
• Build automated pipelines to simulate campaign performance and forecast outcomes.
• Monitor real-time budgets and ensure scalable, maintainable production services.
• Lead CI/CD standards and promote telemetry-first data practices.
• Mentor senior engineers and translate business goals into technical roadmaps.
• Collaborate with product and Applied Scientists on GenAI patterns.

Skills

Databricks Platform

Unity Catalog

MLflow

PySpark

Python

SQL

Time-series forecasting

Leadership

Education

Bachelor's or Master's in CS/Engineering

PhD preferred

Tools

Databricks

Kafka

Kinesis

Job description

Cardlytics is seeking a Senior Principal Data Engineer (IC6) to lead the design and implementation of an enterprise-scale MLOps and forecasting platform built on the Databricks Data Intelligence Platform. You will bridge data science and production engineering, delivering scalable pipelines and real-time budget predictions.

The role emphasizes architecture leadership, telemetry-driven development, and close collaboration with Applied Scientists and business stakeholders to align technical work