Salary Range $123,000 - $160,000* Job Description:

The Data Engineer will play a pivotal role within the Machine Learning team at Saks Fifth Avenue, focusing on designing, implementing, and optimizing sophisticated data workflows tailored to our fast-paced marketing environment. Utilizing advanced skills in Airflow deployed on Kubernetes, you will develop, enhance, and oversee robust pipelines that integrate diverse and complex marketing data sources, including advanced customer segmentation models, campaign analytics, and multichannel advertising insights. Your responsibilities include ensuring seamless data delivery to analytics platforms, proactively improving data reliability and performance, and working closely with stakeholders to drive strategic marketing decisions through high-quality data.

Role Description

Design, implement, and optimize scalable data pipelines using Apache Airflow on Kubernetes to support advanced marketing analytics and customer segmentation initiatives Integrate, manage, and transform complex data streams from diverse marketing sources (e.g., Google Analytics, Salesforce Marketing Cloud, Facebook Ads) to ensure seamless delivery to analytics platforms Develop and maintain robust ETL workflows and data warehousing solutions, leveraging advanced SQL and Python scripting to automate and enhance data processing Proactively monitor, troubleshoot, and improve data reliability, pipeline performance, and data integrity, addressing complex data issues and bottlenecks Collaborate closely with marketing stakeholders and cross-functional teams to deliver high-quality, actionable data for strategic decision-making in a fast-paced environment Contribute to the adoption of best practices in data quality, compliance, and continuous delivery, with opportunities to influence cloud architecture, real-time data integration, and luxury retail analytics Required Qualifications (Minimum Requirements): Bachelor's degree in Computer Science, Information Systems, Engineering, or related technical discipline. 3+ years of professional experience building and managing data pipelines using Apache Airflow, particularly in Kubernetes environments. Extensive experience integrating, managing, and optimizing complex data streams from diverse marketing sources such as Google Analytics, Salesforce Marketing Cloud, Facebook Ads, or similar platforms. Advanced proficiency in SQL, with expertise in data transformation and complex querying. In-depth scripting and automation experience, particularly with Python, for complex data workflows and systems. Comprehensive understanding of data warehousing, dimensional modeling, ETL frameworks, and performance optimization strategies. Proven problem-solving capabilities with an emphasis on diagnosing complex data issues, enhancing pipeline reliability, and ensuring data integrity. Preferred Qualifications: Hands-on experience architecting, deploying, and managing scalable data solutions on cloud platforms such as Google Cloud Platform or AWS. Strong knowledge of streaming technologies, event-driven architecture, and real-time data integration frameworks (e.g., Apache Kafka). Demonstrated expertise in implementing sophisticated data quality processes, validation methods, and compliance standards within marketing analytics. Extensive experience with agile methodologies, CI/CD processes, and continuous improvement practices. Deep understanding of luxury retail analytics, customer lifecycle analytics, and specific business performance metrics relevant to high-end retail environments. Exceptional interpersonal skills, with a proven track record of collaborating effectively with technical teams and business stakeholders.

It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

Saks.com is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

*The above expected salary range may have some variability based upon factors including, but not limited to, a candidate's overall experience, qualifications, and geographic location. If you are interested in the role, we encourage you to apply and, if selected to move forward in the interview process, you will have a chance to speak with our recruitment team regarding your specific salary expectations.