Data Engineer

Responsibilities:

• Contribute to Mail Intelligence Mission:
  Support the development of AI/ML capabilities that enhance user personalization and insights.
• Innovate and Personalize:
  Assist in building scalable solutions that identify user interests and habits, contributing to personalized user experiences.
• Data Pipeline and Insights Development:
  Design and implement robust data pipelines using frameworks like Data Proc, Dataflow, and Composer. Streamline data processing and orchestration, utilize Data Lake and Pub/Sub for storage and streaming, and create insightful visualizations with Looker Studio to support AI/ML initiatives.
• Code Comprehension & Integration:
  Read, analyze, and work with existing Java codebases to understand upstream/downstream services and integrate data pipelines seamlessly.
• Collaboration:
  
  Work closely with cross-functional teams in the USA to integrate data solutions that enhance user experiences.

• Educational Background:
  You have a strong foundation in computer science, data engineering, or a related field, with a focus on big data technologies and cloud platforms.
• Technical
  
  Skills:
  
  You are proficient in programming languages such as SQL, Python,
  must have practical knowledge of Java (specifically the ability to read, trace, and understand Java code), alongside experience with big data frameworks like Hadoop, Spark, or Kafka. You excel in using stream and batch processing frameworks and data visualization tools, and are skilled in implementing data governance practices.

• Educational Requirement:
  Bachelor's degree in Computer Science, Data Engineering, or a related field; a Master's degree is a plus.
• Experience:
  
  5+ years in data engineering, big data processing, or a related field.
• Technical Proficiency:
  Strong skills in SQL, Python, or Java, with experience in big data technologies like Hadoop, Spark, or Kafka.
• Mandatory Java proficiency:
  Strong ability to read, debug, and understand Java source code and architecture.