Data ENGINEER (1110530)
Columbus, OH
Salary: Depends on Experience Description Job Summary: The Decision Engine Team is seeking a skilled and motivated Data Engineer to support the development and optimization of real-time, personalized customer engagement strategies. This role combines the technical rigor of data engineering with the strategic focus of marketing and decision science, enabling the delivery of targeted, data[1]driven messages across multiple customer channels. As a Data Engineer on this team, you will be responsible for building and operationalizing data pipelines, ensuring data quality, and supporting the infrastructure that powers decision engine capabilities. You will collaborate closely with marketing strategists, analysts, and IT to ensure seamless integration and performance of automated messaging systems. Key Responsibilities- Design, build, and maintain scalable and efficient data pipelines to support real-time decisioning and marketing strategies.
- Collaborate with cross-functional teams including marketing, analytics, modeling, and IT to deploy and optimize customer messaging across channels.
- Ensure data quality and integrity through rigorous testing, validation, and monitoring processes.
- Support the integration and enhancement of decision engine platforms such as IBM Unica Interact, Adobe Campaign, or Salesforce.
- Automate data workflows and reporting using tools such as SQL, Python, AWS Glue, or Tableau.
- Participate in the development and deployment of new capabilities and upgrades to decision engine software.
- Assist in troubleshooting and resolving data-related issues in production environments.
- Contribute to the governance and cataloging of curated data assets for enterprise-wide reuse.
- Master’s degree in computer science, engineering, statistics, economics or related fields.
- 3+ years of work and/or educational experience in data engineering, data integration, data quality roles utilizing machine learning or cloud computing to solve complex business problems, scripting languages and packages, scalable data pipelines and big data analysis tools and techniques.
- Proficiency in SQL and at least one programming language such as Python, R, or SAS.
- Familiarity with cloud-based data tools (e.g., AWS Glue, Athena, Lambda) and BI tools (e.g., Tableau, Excel).
- Strong communication skills and ability to work effectively across technical and non-technical teams.
- Hands-on data testing experience and experience with data quality frameworks.
- Experience with open-source and commercial data science platforms.
- Familiarity with Agile methodologies and DevOps practices including version control, automated builds, and release management.
- Experience designing and managing data pipelines for large, heterogeneous datasets.
- Strong data mining and database experience (e.g., MySQL).
- Experience with campaign management or decision engine platforms (e.g., IBM Unica, Adobe Campaign, Pega, Salesforce).
- Ability to communicate complex results to both technical and non-technical audiences.
- Experience in financial services or consumer-centric industries.
- Strong analytical and problem-solving skills with a progressive mindset.
- Willingness and ability to learn new technologies on the job.
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