Data Engineer

You will also be expected to have a hands-on approach towards application development, particularly with the Microsoft Azure suite.

Responsibilities:

• Develop and maintain advanced analytics solutions using tools such as Apache Kafka, Apache Pig, Apache Spark, and AWS Technologies.
• Work extensively with Microsoft Azure suite for application development.
• Implement algorithms and develop APIs.
• Handle integration of complex data sources for decision support systems in the enterprise data warehouse.
• Utilize Cloud Technologies and Data Visualization tools to enhance business intelligence.
• Work with various types of data including Clinical Trials Data, Genomics and Bio Marker Data, Real World Data, and Discovery Data.
• Maintain familiarity with key industry best practices in a regulated “GXP” environment.
• Work with commercial pharmaceutical/business information, Supply Chain, Finance, and HR data.
• Leverage Apache Hadoop for handling large datasets.
• Proficiency in Apache Kafka is expected for efficient real-time data processing.
• Familiarity with Apache Pig is required for handling large data sets.
• Mastery of Apache Spark is essential for large-scale data processing tasks.
• Knowledge of Cloud Technologies is necessary for managing and storing large data sets.
• Ability to perform Data Visualization to represent data in a clear and understandable manner.
• Experience with Algorithm Implementation to solve complex data problems.
• Strong background in Analytics to interpret complex data.
• Competence in Apache Hadoop for storing and processing large data sets.
• Expertise in API Development for seamless data integration.
• Proficiency in AWS Technologies for managing cloud-based data storage and processing.