Job Openings at TalentUp Africa – Apply Now

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 help customers learn and use AWS services such as Redshift, Database Migration Service, Glue, S3, and Schema Conversion Tool.
• You will deliver on-site technical engagements with customers. This includes participating in pre-sales on-site visits, understanding customer requirements, contributing to internal Area of Depth (AoD) programs, authoring AWS Data Analytics best practice blogs/whitepaper and creating packaged data service offerings.
• You will work on short on-site projects to assess and optimize the customer’s Amazon Redshift implementations and help customers to migrate from their existing on-premises data warehouses using other databases to Amazon Redshift.
• You will work with the customer’s business and technology stakeholders to create a compelling vision of a data-driven enterprise in their environment.

Your Profile
Qualification And Experience

• Bachelor’s degree in Computer Science, Engineering, Mathematics or a related field or equivalent professional or military experience.
• AWS Solutions Architect Associate or Professional and the AWS Data Analytics or Machine Learning Specialty Certification.
• 8+ years of experience of IT platform implementation in a technical role.
• 8+ years of development and/or DBA experience in Relational Database Management Systems (RDBMS).
• 5+ years of hands-on experience in implementation and performance tuning MPP databases (Teradata, Vertica, Netezza, Greenplum).
• Experience with prioritization of projects that mitigate trade-offs.
• Experience in analyzing Data Warehouses such as Teradata, Netezza, Oracle, etc. or Greenplum etc.
• Experience designing database environments, analyzing production deployments, and making recommendations to optimize performance.

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Job Description

• In this role, you will work on large-scale data science/data analytics projects.
• Ability to lead effectively across organizations.
• You will Implement AWS services in a variety of distributed computing, enterprise environments.
• You will define system architectures and explore technical feasibility trade-offs.
• You will work on a code base with many contributors.
• You will be required to prototype and evaluate applications and interaction methodologies.
• You will be required to present complex technical information in a clear and concise manner to a variety of audiences therefore you will demonstrate written and verbal technical communication skills.

Your Profile

Qualification And Experience

• Bachelor’s degree, or equivalent experience, in Computer Science, Engineering, Mathematics or a related field
• 1+ years’ experience of Data platform implementation, including 1+ years of hands-on experience in implementation and performance tuning Kinesis/Kafka/Spark/Storm implementations.
• 3+ years experience developing cloud software services and an understanding of design for scalability, performance and reliability.
• 1+ years of IT platform implementation experience.
• Hands-on experience with Data Analytics technologies such as AWS, Hadoop, Spark, Spark SQL, MLib or Storm/Samza.
• 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).
• Proficiency with at least one of 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 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
• Experience building large-scale machine-learning infrastructure that have been successfully delivered to customers.
• Experience with AWS technology stack and current hands-on implementation experience required

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