Overall Job Summary

The Data Engineer for Marketing will work in Python programming and SQL along with extensive experience with Alteryx and Adobe products. This role involves developing, maintaining scalable data pipelines, and collaborating closely with cross-functional teams to support data-driven decisions.

Location: Nashville/Brentwood, TN

Hybrid:  On-Site 3 days/weekly

Essential Duties and Responsibilities (Min 5%) Design, construct, install, test, and maintain highly scalable data management systems. Develop high-quality data pipeline solutions using Python, Spark, and SQL. Ensure optimal data delivery architecture is consistent throughout ongoing projects. Work closely with analytics and business teams to assist with data-related technical issues and support data infrastructure needs. Utilize Adobe tools for data visualization and analysis. Implement data flow automation for efficient data extraction, transformation, and loading (ETL) processes. Analyze and organize raw data, evaluate business needs, and implement suitable data models. Work with stakeholders to assist with data-related technical issues and support their data infrastructure needs. Required Qualifications

Experience:  3 - 5 years experience in related field.  

Education: Bachelor's degree in computer science, Engineering, or related field.  Any suitable combination of education and experience will be considered.

Professional Certifications:  None. 
 

Preferred knowledge, skills or abilities Proven experience as a Data Engineer or similar Data related role. Expertise in Python programming and SQL and analytics tools such as Alteryx and PowerBI. Strong expertise in ETL pipelines and API connections. Direct experience with large-volume customer data sets. Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement. Familiarity with personalization suits like Adobe Campaign, Adobe Target, AEM. Experience connecting multiple disparate data sources to support analytics processes and tools. Experience with big data tools and cloud-based analytical tools (MS Azure, Snowflake, Kafka, or similar). Experience building and optimizing data pipelines, architectures, and data sets. Strong analytic skills related to working with unstructured datasets. Solid understanding of SQL, NoSQL, and other database technologies. Excellent problem-solving and communication skills.

#LI-DNI

Working Conditions Normal office working conditions Physical Requirements Sitting Standing (not walking) Walking Lifting up to 10 pounds Disclaimer

This job description represents an overview of the responsibilities for the above referenced position.  It is not intended to represent a comprehensive list of responsibilities.  A team member should perform all duties as assigned by his/ her supervisor.