Job Description

• In this role, you’ll work with innovative builders who are pushing the boundaries of cloud technology. You’ll get to be bold, think big, and make an impact on your career. You’ll be encouraged to bring your experiences, talents, and passions to work.
• You will work with the client’s customers and focus on their AWS Analytics and ML service offerings such as Amazon Kinesis, AWS Glue, Amazon Redshift, Amazon EMR, Amazon Athena, Amazon Sagemaker, and more. Help customers to remove the constraints that prevent them from leveraging their data to develop business insights.
• You will engage in a wide variety of projects for customers, providing collective experience from across the AWS customer base, and are obsessed with customer success.
• You will develop and define key business questions and build data sets that answer those questions.

Qualification and Experience

• Bachelor’s degree, or equivalent experience, in Computer Science, Engineering, Mathematics, or a related field.
• 5+ years’ experience in Data platform implementation, including 3+ years of hands-on experience in implementation and performance tuning Kinesis/Kafka/Spark/Storm implementations.
• Two (2) AWS Certification(s) at the associate, professional, or specialty certification offered by Amazon Web Services and 1 AWS certification in progress with expected completion in 1 month.
• Experience with analytic solutions applied to the Marketing or Risk needs of enterprises.
• Basic understanding of machine learning fundamentals.
• Ability to take Machine Learning models and implement them as part of the data pipeline.
• Experience with one or more relevant tools ( Flink, Spark, Sqoop, Flume, Kafka, Amazon Kinesis).
• Experience developing software code in one or more programming languages (Java, JavaScript, Python, etc).
• Current hands-on implementation experience required.
• Experience with design, development, and operations that leverage deep. knowledge in the use of services like Amazon Kinesis, Apache Kafka, Apache Spark, Amazon Sagemaker, Amazon EMR, NoSQL technologies, and other 3rd parties.