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Responsibilities:Lead the growth of Data and Analytics practice for Financial Services and InsuranceProvide technical expertise and guidance on the selection, and hands-on implementation, and optimization of big data platforms, tools, and technologies across multiple cloud environments (e.g., AWS, Azure, GCP, Snowflake, etc.
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Minimum of fifteen years of overall technical experience in solution architecture, design, hands-on development with a focus on big data technologies, multi-cloud platforms, and with at-least ten years of experience specifically in financial services.
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Big Data Expertise : 3+ years of hands-on experience with major Big Data technologies and frameworks, including Spark, Hive, ZooKeeper, HDFS, Presto, Hadoop, MapReduce, Tensorflow, and more.
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Hands-on experience with big data technologies, including Apache Spark and Databricks Delta Lake. Proven experience as a Data Engineer with a focus on Databricks.
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Expertise in Cloudera Big Data Technologies, including Cloudera Distribution of Hadoop (CDP), Apache Hadoop, Apache Spark, Apache Hive, Apache Impala, and Apache HBase, with hands-on experience in deploying, configuring, and optimizing these technologies for large-scale data processing and analytics.
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Data Warehouse and Big Data Experience: Possess hands-on experience in designing and maintaining data warehouses and/or data lakes using big data technologies such as Hadoop, Spark, and especially DataBricks.
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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, The ideal candidate will lead the architecture and implementation of on-premises and cloud big data solutions as part of enterprise data modernization.
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Self-driven, challenge-loving, detail oriented, teamwork spirit, excellent communication skills, ability to multitask and manage expectationsNice to have:Experience in any of: machine learning, analytics, data mining, or data mart and warehouseExperience with Deep Learning platforms (Tensorflow/Keras/Spark MLlib) and SQL/Unix/ShellExperience with machine learning algorithms, NLP, and/or statistical methods a big plusYahoo is proud to be an equal opportunity workplace.
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Responsibilities: Technical Leadership: Lead by example, contributing hands-on expertise in Python, Airflow, Snowflake, and AWS to develop scalable and efficient solutions. Job Title: Hands-On Engineering Manager Location: Newton, MA About Us: My client is a rapidly growing eCommerce beverage distribution company that achieved $200 million in revenue last They are at the forefront of revolutionizing the beverage industry by providing exceptional service and innovative solutions.
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Experience with applied machine learning (tree-based methods, ensemble methods, neural networks/deep learning)Proficient understanding of relational (e.g. Oracle, SQL Server, PostgreSQL) and Big Data distributed structures (Hadoop/Spark) in order to source data effectively.
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Hands-on development experience with Design and Architecture of big data frameworks/tools: Azure Data Lake, Snowflake, Azure Data Bricks. Expert in Azure cloud computing, specializing in Azure data engineering stacks like ADF (Azure Data Factory), ADLS, Event Hubs, Snowflake, Databricks, streaming, Azure PowerShell, and Log Analytics.
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Experience with NoSQL databases such as mongoDB, Cassandra or similar is a plusMinimum of 4 years of experience in developing data ingestion, data processing and analytical pipelines for big data, relational databases, NoSQL, data lake and data warehouse solutionsMinimum of 4 years of hands-on experience in Big Data technologies such as, PySpark, Spark/SparkSQL, Dask or similar distributed compute frameworks.
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Including hands on experience with productionized data ingestion and processing pipelines using Python, Data bricks, Snow SQLExcellent understanding of Snowflake Internals and integration of Snowflake with other data processing and reporting technologiesExcellent presentation and communication skills, both written and verbal, ability to problem solve and design in an environment with unclear requirements.
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Hands-on experience with Spark or ScalaGood experience in end-to-end implementation of data warehouse and data martsPreferred Qualifications: Strong understanding of databases and big data software technologies, specifically Azure and Databricks.
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Required 10 Years Hands-on experience with Azure services such as Azure Data Factory, Azure Databricks, Azure Data Lake Storage, Azure SQL, Azure Synapse Required 5 Years Hands-on experience in SQL Server (SSIS, SSRS, SSAS), ORACLE, T-SQL Required 10 Years Hands-on experience in Azure SQL Database, Azure SQL Datawarehouse Required 7 Years Hands-on experience in deploying and maintaining large-scale data processing pipelines.
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hands on big data jobs Company: Directv in West-greenwich, Rhode Island
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