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Build and deploy batch and streaming pipelines to collect and transform our rapidly growing Big Data set within our hybrid cloud architecture utilizing Kubernetes/EKS, Kafka/MSK, and Databricks/Spark.
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The main digital solutions used in supporting the various business cycles, beyond the standard SAP applications, are Robotic Process Automation (RPA) and Advanced Analytics technologies including SAP Business Warehouse (BW) and SAP Analytics Cloud (SAC.
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Expertise in major cloud platforms such as AWS, Azure, and Google Cloud Platform (GCP) As a Senior Cloud Data Architect, you will be responsible for designing secure and scalable architecture solutions to safeguard our organization’s critical information assets.
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Hands on custom SAP Commerce Cloud / SAP Hybris development experience on both Front-End and Back-End. SAP Commerce Cloud/Hybris Technical Lead. Front end development – Vue JS, React JS, Node JS, Angular JS, JavaScript, CSS, HTML, etc.
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Establish strong software engineering principles for development in Python on the Azure/Google Cloud Platform. Position SummaryAs a Lead ML/AI Engineer, you will drive the design and implementation of functionality related to the end-to-end ML/AI and Feature lifecycle management on Azure/Google Cloud Platform, leveraging and integrating the cloud native services with other standard operational and automation tools.
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Experience with cloud technologies and migrations Working knowledge of DevOps tools. Experience developing and delivering technical solutions using public cloud service providers like Amazon, Google, etc.
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Minimum of 3 years of building and operationalizing large-scale enterprise data solutions using one or more third-party resources such as Pyspark, Talend, Matellion, Informatica or native utilities as Spark, Hive, Cloud DataProc, Cloud Dataflow, Apache, Beam Composer, Big Table, Cloud BigQuery, Cloud PubSub etc.
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10+ years of progressive experience in software engineering with an understanding of large-scale computing solutions (Primarily AWS), including software design and development, database architectures, IP networking, security, cloud operations, and performance tuning.
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Automate and abstract the code-to-deployment workflow for microservices on the Google Cloud Platform (GCP) Knowledge of public cloud platforms (AWS, GCP, Azure) and key platforms like Kubernetes (k8s) and VMs.
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The ideal candidate will possess a deep understanding of cloud security, automation, and DevSecOps practices. Relevant industry certifications, such as CCSP, CISSP, or vendor-specific cloud security certifications.
$120,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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TDD, CI/CD, Distributed Computing, Linux Stack, MLOps, Machine Learning Operations, HPC, High Performance Computing, AWS, GCP, Cloud, Trading, Financial, Remote, Work From Home, Chicago Recruiters, Information Technology Jobs, IT Jobs, Chicago RecruitingLooking to hire for similar positions in Chicago, IL or in other cities.
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Advanced proficiency in the design and implementation of modern data architectures and concepts such as cloud services (e.g., AWS, Azure, GCP), real-time data distribution (e.g., Kafka, Kinesis, DataFlow, Airflow), NoSQL (e.g., MongoDB, DynamoDB, HBase, CosmosDB) and modern data warehouse tools including Snowflake and DataBricks.
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Ideal candidate will have a development background alongside experience automating build and deployment pipelines in Azure for multiple services and supporting middleware such as AKS and Databricks in the cloud.
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Knowledge, Skills & Abilities Experience designing, implementing, and supporting applications in Amazon Web Services (AWS) cloud, including traditional server applications and serverless services such as AWS Lambda, AWS Fargate, AWS SQS, and Amazon API Gateway.
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Job description Infosys is seeking an Azure Databricks Cloud Data Architect. At least 7 years of Information Technology experienceHands on experience in architecting Cloud data solutions using Azure Synapse, Databricks, Python, PySpark, SQLSignificant experience with Cloud Data lake technologies and complex data architecture and models.
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