Objective of the Role: The Data Engineer for Personalization is responsible for designing, building, and maintaining the data infrastructure that enables real-time user experience personalization. This role is pivotal in developing data pipelines that feed into personalization algorithms, allowing for a unique and optimized user experience. Additionally, it supports data science and marketing teams by ensuring access to critical data for implementing personalized strategies, directly impacting customer satisfaction, retention, and conversion rates. The role involves continuously analyzing and adjusting personalized notification strategies based on user behavior and advanced segmentation, ultimately driving user retention and conversion while aligning notifications with business objectives to maximize revenue and engagement.
Key Responsibilities:
- Design and maintain real-time data pipelines that gather relevant user information, including behavior, purchase history, and preferences, to power personalization algorithms.
- Implement data storage architectures that allow for fast access and processing of large data volumes using Big Data technologies (e.g., Spark, Hadoop).
- Develop and maintain optimized data models to enable user segmentation and personalization across multiple channels, including web, email, and push notifications.
- Support Data Scientists by providing access to processed and structured data, facilitating the implementation of machine learning models for personalization.
- Ensure data integrity and user privacy in compliance with regulations such as GDPR, utilizing advanced data security and privacy protocols.
- Propose continuous improvements in personalization infrastructure, aligning with industry best practices to optimize the customer experience.
Requirements:
Education:
- Bachelor’s degree in Marketing, Communication, Business Administration, Systems Engineering, or related fields with a focus on digital marketing.
Languages:
- Intermediate proficiency in English required.
Certifications and Specialized Knowledge:
- Bachelor’s degree in Computer Science, Systems Engineering, Applied Mathematics, or related fields.
- Specialization in Data Engineering or certification in cloud platforms is ideal.
Work Experience:
- 3 to 5 years of experience in data engineering roles, ideally involving personalization projects, machine learning, or recommendation systems.
- Proficiency in programming languages such as Python and Scala, and experience with real-time processing frameworks (e.g., Apache Kafka, Spark Streaming).
- Experience in designing and managing Big Data databases (e.g., AWS Redshift, Google BigQuery) and cloud architectures.
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