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Proficiency in data technologies, such as relational databases, data warehousing, big data platforms (e.g., Hadoop, Spark), data streaming (e.g., Kafka), and cloud services (e.g., AWS, GCP, Azure.
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Proven capability in data engineering or data science, with practical experience using AWS SageMaker and other industry-standard data analytics tools. Smoothstack is recruiting for a Senior Software Engineer with a strong focus in Data Science and significant hands-on experience in Cloud Native development to drive the creation of next-generation, data-driven applications.
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Data Integration, AWS Cloud services (Lambda, Glue, Redshift, Athena) Expertise in AWS Cloud services (Lambda, Glue, Redshift, Athena) AWS Cloud services (Lambda, Glue, Redshift, Athena.
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Utilize programming languages like Scala, Java, Python, SQL and GO and NoSQL databases and Cloud based data warehousing services such as Redshift and Snowflake. At least 1 year experience with cloud computing (AWS, Microsoft Azure, Google Cloud.
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5+ years of experience with a public cloud (AWS, Microsoft Azure, Google Cloud) As a Capital One Senior Lead Data Engineer, you’ll have the opportunity to be on the forefront of driving a major transformation within Capital One.
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12+ years of experience in IT infrastructure, with at least 3-4 years in cloud architecture and hands-on provisioning of modern Data platforms like Databricks on AWS cloud.
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In-depth knowledge of big data technologies such as Hadoop, Spark, Kafka, and cloud platforms such as AWS, Azure, GCP, Snowflake, Databricks, etc. Preferred Qualifications:Professional certifications in cloud computing (e.g., AWS Certified Solutions Architect, Microsoft Certified Azure Solutions Architect, Azure Data Engineer, SnowPro Core) and/or big data technologies.
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Experience of implementing Amazon EMR or Big Data technologies like Hadoop, Spark, Presto, Hive will be a plus. Implementation experience of Big Data technologies like Hadoop, Spark, Presto, Hive, and Hue will be a major advantage.
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Utilize programming languages like Java, Scala, Python and Open Source RDBMS and NoSQL databases and Cloud based data warehousing services such as Redshift and Snowflake. 4+ years of experience with a public cloud (AWS, Microsoft Azure, Google Cloud.
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5+ years hands-on experience with building cloud production data solutions leveraging services and technologies such as AWS EC2, S3, Redshift, RDS, Glue, Athena, Demonstrated on-the-job experience with large-scale data migration from Oracle on prem to AWS Cloud environment.
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1- 3-years minimum professional experience in cloud data engineering and science and associated technologies utilizing cloud data platforms such as Databricks, AWS RedShift, and Snowflake.
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Experience in Data science, machine learning, or optimization models Experience in Python, Spark, Scala, or R, using open source frameworks (for example: scikit learn, TensorFlow, Pytorch) You are knowledgeable of databases, data warehouse design, cloud storage, and ETL best practices.
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Experience in AWS Cloud Technologies Proficiency with Python, Java, shell scripting (Bash and PowerShell) & SQL Experience working with storage management, streaming data, and data extraction from different databases (Oracle, DB2, MySQL, RDS and NoSQL etc.
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Experience with cloud services: AWS, Azure , GCP, etc. Experience with cloud services: AWS, Azure, GCP, etc. Experience with modern data tools: Snowflake, BigQuery, dbt, Airflow, dagster, Fivetran etc.
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Minimum 2 years of experience in development using Data warehousing, Big Data Eco System Hive (Hql) & Oozie Scheduler, ETL IBM Data Stage, Informatica IICS with Teradata 1 Year experience of deploying google cloud services using Terraform.
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big data science aws cloud jobs Company: Capital One
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