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3+ years of experience with a public cloud (e.g., Microsoft Azure, AWS, Google Cloud). 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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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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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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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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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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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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Leverage modern ML/NLP methodologies (e.g., deep learning), computing hardware (e.g., GPUs), cloud infrastructure (AWS/Azure), open-source modeling frameworks (e.g., TensorFlow, Keras, PyTorch, XGBoost.
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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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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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Understanding and experience with modern cloud data warehouse and engineering for one or more of the following cloud providers - Azure (ADF, Synapse, Power BI), AWS (Glue, Redshift, Sagemaker), GCP (BigQuery, Vertex, Cognitive Services), Snowflake, Tableau.
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Using tools such as Snowflake and/or Databricks, they will also work with cutting-edge DevOps technologies, develop advanced analytics products, and apply data and statistical programming tools to enterprise data to advance and enable key mission outcomes within cloud environments (GCP, AWS, Azure.
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Advanced knowledge of cloud computing technologies such as: Apache Spark, Azure Data Factory, Azure DevOps, Azure ML (Machine Learning), Hadoop, Microsoft Azure, Databricks, AWS, Google Cloud.
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Leverage a broad set of modern technologies – including Python, R, and Spark – to analyze and gain insights within large data sets. Demonstrates advanced functional knowledge of data visualization libraries such as matplotlib or ggplot2; knowledge of other visualization tools such as Microsoft Power BI and Tableau.
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