[job-28508] Sr. Data & ML Engineer, Brazil.

Key Responsibilities 
- Work with our customers and focus on our AWS Analytics and ML service offerings such Amazon Kinesis, AWS Glue, Amazon Redshift, Amazon EMR, Amazon Athena, Amazon Sagemaker and more. Help our customers to remove the constraints that prevent them from leveraging their data to develop business insights
- Create white papers, writing blogs, build demos and other reusable collateral that can be used by our customers. Work closely with our Solution Architects, Data Scientists and Service Engineering teams
- Experience with design, development and operations that leverages deep knowledge in the use of services like Amazon Kinesis, Apache Kafka, Apache Spark, Amazon Sagemaker, Amazon EMR, NoSQL technologies and other 3rd parties
- Develop and define key business questions and to build data sets that answer those questions. You should be able to work with business customers in understanding the business requirements and implementing solutions

Basic Qualifications
- Bachelor’s degree, or equivalent experience, in Computer Science, Engineering, Mathematics or a related field
- 5+ years’ experience of Data platform implementation, including 3+ years of hands-on experience in implementation and performance tuning Kinesis/Kafka/Spark/Storm implementations
- 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 data pipeline
- 5+ years of IT platform implementation experience
- 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

Preferred Qualifications
- Masters or PhD in Computer Science, Physics, Engineering or Math
- Hands on experience working on large-scale data science/data analytics projects
- Ability to lead effectively across organizations
- Hands-on experience with Data Analytics technologies such as AWS, Hadoop, Spark, Spark SQL, Mlib or Storm/Samza
- Implementing AWS services in a variety of distributed computing, enterprise environments
- Proficiency with at least one the languages such as C++, Java, Scala or Python
- Experience with at least one of the modern distributed Machine Learning and Deep Learning frameworks such as TensorFlow, PyTorch, MxNet Caffe, and Keras
- Experience building large-scale machine-learning infrastructure that have been successfully delivered to customers
- Experience defining system architectures and exploring technical feasibility trade-offs
- 3+ years experiences developing cloud software services and an understanding of design for scalability, performance and reliability
- Experience working on a code base with many contributors
- Ability to prototype and evaluate applications and interaction methodologies
- Experience with AWS technology stack
- Written and verbal technical communication skills with an ability to present complex technical information in a clear and concise manner to a variety of audiences.