CONTD FROM H.10B microservice architecture for data platforms.br br Education and Experiencebr br Bachelors degree or foreign education equivalent in Computer Science, Engineering, Information Technology, Information Systems, Mathematics, Physics, or a closely related field and six 6 years of experience in the job offered or six 6 years of experience leading and building highly scalable, Cloudnative, eventdriven, microservice architecture for data platforms.br br Or, alternatively, Masters degree or foreign education equivalent in Computer Science, Engineering, Information Technology, Information Systems, Mathematics, Physics, or a closely related field and four 4 years of experience in the job offered or four 4 years of experience leading and building highly scalable, Cloudnative, eventdriven, microservice architecture for data platforms.br br Skills and Knowledgebr br Candidate must also possessbr br Demonstrated Expertise DE performing architecture design developing and providing guidance to implement a highperformant and scalable recommendation engine that serves personalized content across Workplace Investing WI channels on Amazon Web Services AWS, using Drools, EKS, Sagemaker, Spark, S3, Lambda, Cassandra, Kafka, and Java.br br DE acting as a member of a team responsible for implementing data lake strategies to leverage Snowflake as a platform for structured and semistructured data; and building and formulating data lake design patterns for data ingestion, processing, and extraction for personalization teams, using Snowflake, SQL, Python, Apache airflow, SQSSNS, S3, CloudFormation, Jenkins, and Datadog.br br DE building WI AIML platforms creating model ready feature database stores in Snowflake; building and deploying supervised and deep learning AIML models, using Sagemaker, EKS, AWS Lambda, and Python; recommending content to drive clickrates using AIML libraries and algorithms Multi Arm Bandit, ChampionChallenger, and userbased similarity model; and querying AWS Neptune graph database that store complex customer attribute relationships using Apache Gremlin.br br DE performing data analytics designing and building measurement analytical platforms that view recommendation success in real time and measure drift and decay using Sagemaker, Snowflake, and Tableau dashboards.
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