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At least 1 year experience with cloud computing (AWS, Microsoft Azure, Google Cloud) 4+ years of experience with AWS, GCP, Microsoft Azure, or another cloud service. Utilize programming languages like JavaScript, Java, HTML/CSS, TypeScript, SQL, Spring Boots, Angular and Open Source RDBMS and NoSQL databases, Container Orchestration services including Docker and Kubernetes, and a variety of AWS tools and services.
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Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and containerization technologies (e.g., Docker, Kubernetes) and their health data exchange and storage frameworks. Lead efforts collaborating with a cross-functional team in designing, configuring, and implementing digital data exchange solutions using integration platforms like CloverLeaf, Rhapsody, Mirth Connect, or similar technologies to support various data exchange protocols and standards used in healthcare, such as HL7, FHIR, DICOM etc.
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3+ years of experience with AWS, GCP, Microsoft Azure, or another cloud service. 7+ years of experience in at least one of the following: JavaScript, TypeScript, SQL, Node.js, or Vue.js. Utilize programming languages like JavaScript, Java, HTML/CSS, TypeScript, SQL, Python, and Go, Open Source RDBMS and NoSQL databases, Container Orchestration services including Docker and Kubernetes, and a variety of AWS tools and services.
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Implement data processing pipelines using Azure Data Factory, Databricks, Azure Machine Learning, Azure Logic Apps, Azure Function Apps, Azure Kubernetes container and other big data services.
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Proficiency in data storage technologies such as relational databases (e.g., PostgreSQL, MySQL), NoSQL databases (e.g., MongoDB, Cassandra), data warehouses (e.g., Snowflake, Redshift), and data lakes (e.g., Amazon S3, Azure Data Lake Storage.
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Data Warehousing Guru: Familiarity with data warehousing solutions like ClickHouse, Redshift, BigQuery, or Snowflake for efficient data storage and retrieval. Cloud Native: Hands-on experience utilizing cloud platforms (AWS, Azure, GCP) for data processing, storage, and orchestration, optimizing for performance and cost.
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Designing and developing large-scale data solutions using GCP services like DataProc, Dataflow, Cloud Bigtable, BigQuery, Cloud SQL, Pub/Sub, Cloud Data Fusion, Cloud Composer, Cloud Functions, Cloud storage, Compute Engine, Looker, Cloud IAM, etc.
Full-timeExpandApply NowActive JobUpdated 26 days ago - UpvoteDownvoteShare Job
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Experience with cloud and modern data science tools and platforms such as Databricks MLFlow, GCP BigQuery, AWS SageMaker, Kubeflow, and Azure ML. You have hands-on expertise with leading technologies for building applications powered by Python, cloud technologies (AWS, Azure, GCP), and may have AI expertise.
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Experience with Azure and AWS cloud security principles and technologies. Professional Cyber Security Certification Required (e.g., CISSP, CCSP, SSCP, CEH or equivalent.) Experience with security tools and technologies such as firewalls, SIEM (Splunk), IDS/IPS, DLP, endpoint security, etc.
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Redshift, BigQuery, Postgres, Mongo, Redis; Our team is made up of over 500 employees globally, and our work for brands like Apple, Athleta, Best Western Hotels & Resorts, Kohler, McDonald’s, Nike, Old Navy, Sephora and Shake Shack runs across 85+ countries and has received top industry recognition from Cannes Lions to Adweek Media Plan of the Year.
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Required Skills & Experience 3+ years of experience Python SQL Snowflake Azure Desired Skills & Experience Strong Data Lake Experience Interest, exposure or experience within cyber security You will receive the following benefits: Medical & Dental Insurance Health Savings Account (HSA) 401(k) Paid Sick Time Leave Pre-tax Commuter Benefit Potential For Conversion to Full-time Applicants must be currently authorized to work in the United States on a full-time basis now and in the future.
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The Senior End User Services (EUS) Engineer performs level 3 support, research, policy development, MECM/Intune software packaging, configuration management, imaging, Microsoft & 3rd party patch management and new technologies for the End-User Services environment including the Azure GCC High cloud environment.
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Implement automation and infrastructure-as-code practices using tools such as Azure Resource Manager (ARM) templates, Terraform, or Azure DevOps pipelines to streamline deployment and management of Azure resources.
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Build automation for CI/CD and SaaS API delivery on AWS, Azure, Elastic and Snowflake. As an integral part of our team, you will not only need to tackle operational challenges at every layer of the system infrastructure, but also set up essential tools like Spark, Databricks, Snowflake, Kubernetes, and Kafka for data science infrastructure.
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Knowledge of data query languages like SQL, and of cloud-based MS Azure Databricks use in modeling. Master’s Degree in Statistics, Data Science, Applied Mathematics, Econometrics, Finance, Operations Research, Industrial Engineering, Physics, Computer Science, or similar quantitative field required.
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