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Utilize programming languages like Java, Python, SQL, Node, Go, and Scala, Open Source RDBMS and NoSQL databases, Container Orchestration services including Docker and Kubernetes, Application Architecture like microservices, API, and realtime streaming, ETL and Data Engineering technologies like PySpark, Glue, Snowflake, and a variety of AWS tools and services.
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Utilize programming languages such as Java, Python, SQL, Node, Go, and Scala, 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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Infrastructure Provisioning and Orchestration: Architect and deploy scalable infrastructure for ML workloads using cloud platforms (e.g., AWS, Azure, Google Cloud) and containerization technologies (e.g., Docker, Kubernetes.
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Utilize programming languages like Java, Python, SQL, Node, Go, and Scala, 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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Therefore, we prioritize individuals coming from the following communities: Refugee, Neurodivergent, Single Parent, Blind or Low Vision, Deaf or Hard of Hearing, Black, Hispanic, Asian, Military Veterans, the Elderly, the LGBTQ, and Justice Impacted individuals.
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Utilize programming languages like Java, Python, Scala and Container Orchestration services including Docker and Kubernetes, and a variety of Azure tools and services across the software development life cycle (task management, source code, building, deployment, operations, real-time communication) to perform advanced-level Java application design implementation, and maintenance under minimal direction.
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5+ years of experience in at least one of the following: Java, Scala, Python, Go, or Node.js. Senior Software Engineer Backend (Python, SQL, ETL, Spark, AWS) page is loaded Senior Software Engineer Backend (Python, SQL, ETL, Spark, AWS) Apply locations McLean, VA New York, NY time type Full time posted on Posted 2 Days Ago job requisition id R184311 Center 1 (19052), United States of America, McLean, VirginiaSenior Software Engineer Backend (Python, SQL, ETL, Spark, AWS) Do you love building and pioneering in the technology space.
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At least 1 year experience with cloud computing (AWS, Microsoft Azure, Google Cloud) The Data Product Interface (DPI) team in Capital One is disrupting existing data access patterns to optimize and elevate data access to Data Products within Capital One. Our cutting edge system is built using modern tech stacks and deployed in the Cloud as a platform to meet Enterprise needs.
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This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Lead Software Engineer, Back End (Golang, AWS) San Francisco, California (Hybrid On-Site): $213,400 - $243,500 for Lead Software Engineer.
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Utilize programming languages like Java, Python, SQL, Node, Go, and Scala. Work on public cloud infrastructure, Big data technologies, 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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Lead Software Engineer, Full Stack, (Java, Golang) As a Capital One Lead Software Engineer, you’ll have the opportunity to be on the forefront of driving a major transformation within Capital One. At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors, who love to solve real problems and meet real customer needs.
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Experience with Docker, Kubernetes, Microservices Architecture, Hadoop, Spark, Databricks, Airflow, NiFi, Lucene, Solr, OpenSearch. Experience in at least two of the following programming languages: Java, Scala, JavaScript, Python, Golang, Bash, Ansible, Terraform.
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7+ years of experience in at least one of the following: Java, Scala, Python, Go, or Node.js. Software Engineering Manager. 2+ years of experience with AWS, Google Cloud Platform, Azure, or another cloud service.
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Software Engineering & DevOps: Version Control: Familiarity with tools like Git. Continuous Integration/Continuous Deployment: Knowledge of pipelines and tools like Jenkins, Travis CI. Containerization: Familiarity with Docker, Kubernetes, etc., for scalable deployment of data science applications.
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Experience with AWS services: EC2, S3, EMR, RDS, Redshift/Spectrum, Lambda, Glue, Athena, API gateway, and design patterns (Containers, Serverless, Kubernetes, Docker, etc.) 3+ years of experience with one or more programming languages, Python, R, SAS, Scala, or Java.
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