About the job
Key Responsibilities
- Collaborate with clients to leverage our AWS Analytics and ML service offerings, including Amazon Kinesis, AWS Glue, Amazon Redshift, Amazon EMR, Amazon Athena, Amazon Sagemaker, and more. Assist clients in overcoming barriers to harnessing their data for insightful business development.
- Produce white papers, write blogs, create demos, and develop other reusable materials for our clients. Work in close partnership with our Solution Architects, Data Scientists, and Service Engineering teams.
- Utilize deep expertise in services such as Amazon Kinesis, Apache Kafka, Apache Spark, Amazon Sagemaker, Amazon EMR, NoSQL technologies, and other third-party solutions for design, development, and operations.
- Formulate and define key business questions and construct datasets that provide answers. Collaborate with business customers to understand their requirements and implement effective solutions.
Basic Qualifications
- Bachelor’s degree or equivalent experience in Computer Science, Engineering, Mathematics, or a related field.
- Over 5 years of experience in Data platform implementation, including at least 3 years of hands-on experience with Kinesis/Kafka/Spark/Storm technologies.
- Proven experience providing analytic solutions for Marketing or Risk needs in enterprises.
- Fundamental understanding of machine learning principles.
- Ability to integrate Machine Learning models into data pipelines.
- Over 5 years of experience in IT platform implementation.
- Familiarity with tools such as Flink, Spark, Sqoop, Flume, Kafka, and Amazon Kinesis.
- Proficient in software development using languages like Java, JavaScript, Python, etc.
- Current hands-on implementation experience is essential.
Preferred Qualifications
- Master’s or PhD in Computer Science, Physics, Engineering, or Mathematics.
- Hands-on experience with large-scale data science and analytics projects.
- Strong leadership abilities across various organizational levels.
- Practical experience with Data Analytics technologies, including AWS, Hadoop, Spark, Spark SQL, Mlib, or Storm/Samza.
- Experience implementing AWS services in diverse distributed computing and enterprise environments.
- Proficiency in at least one programming language, such as C++, Java, or Python.

