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Far Ridgeline Engagements LLC (a QinetiQ US Company) is seeking an experienced cloud data engineer/developer to help lead a growing team with a US Department of Defense operations support project developing modern, cloud-based solutions to empower customers to securely store and analyze data.
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Experience with provisioning virtual resources and building infrastructures in AWS, Google Cloud, Microsoft Azure, and Digital Ocean commercial clouds. Working knowledge of AWS Cloud Formation, JSON, and Python scripting languages.
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Use cutting edge technologies such as Python, Scala, Spark, and a variety of Cloud services to develop modern data pipelines supporting Machine Learning and Artificial Intelligence.
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Big data and cloud computing, including AWS, Azure, GCP, other related, as well as Hadoop, Spark, MapReduce, etc. Database architect with relational databases (e.g. Postgres, MySQL, MSSQL, Oracle) and other modern types of databases: graph, key-value, and document data stores (e.g. Neo4j, HDFS, MongoDB.
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ML skills in modern cloud infrastructure such as Azure, AWS, or GCP is strongly desired. Ankura’s Data & Technology Practice includes client services in the areas of Analytics & Data Strategy, eDiscovery & Cyber Security.
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4+ years of experience with a public cloud (AWS, Microsoft Azure, Google Cloud) - You will develop applications from ground up using a modern technology stack such as Scala, Spark, Postgres, Angular JS, and NoSQL.
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You will continuously integrate and ship code into our on premise and cloud Production environments. - 4+ years of data warehousing experience (Redshift or Snowflake) - 4+ years experience with Distributed data/computing tools (MapReduce, Hadoop, Hive, EMR, Kafka, Spark, Gurobi, or MySQL.
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Experience with cloud technologies (AWS, Azure) a plus7. Experience in modern programming languages like JavaScript, Typescript, Node, Java, Python, etc. Experience with a RDBMS (SQL) or a NoSQL data store a plus4.
$150,000 - $270,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Demonstrated 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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Extensive experience or knowledge of cloud-based data platform technologies such as AWS, Microsoft Azure or Google Cloud Computing. In depth knowledge of modern data technologies including Snowflake, RedShift, Azure SQL/Synaspe, Databricks or similar technologies.
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Advanced knowledge of cloud computing technologies such as: Apache Spark, Azure Data Factory, Azure DevOps, Azure Client (Machine Learning), Hadoop, Microsoft Azure, Databricks, AWS, Google Cloud.
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5+ years of experience with modern Cloud computing technologies: AWS and Microsoft Azure. Experience with cloud AI ML capabilities like AWS, Databricks. Knowledge of modern software design patterns, including microservice design or edge computing.
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Collaborate with DevOps and infrastructure teams to deploy and manage data platforms and services in cloud environments (AWS & Snowflake). You will be responsible for building (leading) end-to-end data pipelines using tools like dbt, airflow, Snowflake, and other modern data stack components.
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Mature AWS cloud solutions with a specific focus on data services such as S3, RDS, and EMR. B.S. in Computer Science (or equivalent experience) and at least 3 years professional experience working as part of an Agile team using DevOps practices and modern programming languages and frameworks to develop and engineer data-related services and applications to cloud platforms.
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Preference for candidate experienced with cloud AI Client capabilities (e.g., AWS, Databricks) Knowledge of modern software design patterns including microservice design and edge computing.
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modern aws cloud jobs Title: data in Mclean, VA
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