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The successful Software Engineer candidate will be part of the KBR team supporting the Test Resource Management Center’s (TRMC) Big Data (BD) and Knowledge Management (KM) Team working on prototype BD and KM systems for DoD test ranges and various acquisition programs.
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Experience in any cloud data warehouse like Synapse, Big Query, Redshift, Snowflake. Implement best practices for data management, security, and governance within the Databricks environment.
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Optimize Databricks jobs for performance and scalability to handle big data workloads. Our challengeThis position is for a Cloud Data engineer with a background in Python, Pyspark, SQL and data warehousing for enterprise level systems.
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Experience with more than one data cataloguing, data governance, data quality, data privacy and master data management (Informatica, Ataccama, Collibra, Alation, Global Ids, Big Id, etc.
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Knowledge of real-time data streaming and real-time analytics Knowledge of Microsoft suite of tools is desired (Power BI, Synapse suite of analytics tools, Azure Data Factory) Strong implementation skills and working knowledge of data structures, algorithms and big data tools (Spark, Hadoop, Python, SQL, NoSQL, Hive); Must have hands-on experience using Spark.
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We are adding privacy features to Apache's big data ecosystem (Spark, Hive Presto), and building world-class data security & privacy framework for big data tech stack.
$175,750 - $266,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Nationwide embraces an agile work environment and collaborative culture through the understanding of business processes, relationship entities and requirements using data analysis, quality, visualization, governance, engineering, robotic process automation, and machine learning to produce targeted data solutions.
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The Database Security Engineer Lead is responsible for implementing and maintaining security systems that provide detection, prevention, containment and deterrence mechanisms to protect the integrity of relational database systems, AWS cloud native databases, NoSQL and big data platforms, and the data they contain.
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Providing guidance and support for data governance, including metadata management, data lineage, and data cataloging. As an Azure Data Engineer, master data integration and ETL tools crucial for seamless data processing.
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In-depth knowledge of Azure cloud data solutions, relational databases, ETL/ELT architecture and concepts, data integration concepts and big data concepts. Designing and implementing scalable and secure data processing pipelines using Azure Data Factory, Azure Databricks, and other Azure services.
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A strong grasp of Microsoft Azure, covering a spectrum of services for seamless deployment, scaling, and management of data solutions, leveraging the power of the cloud. Keeping abreast of the latest Azure features and technologies to enhance data engineering processes and capabilities.
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Design, develop, and deploy Databricks jobs to process and analyze large volumes of data. Role: Databricks Engineer with PySpark exp. Collaborate with data engineers and data scientists to understand data requirements and implement appropriate data processing pipelines.
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Familiarity with big data processing frameworks like Apache Spark or Hadoop. Experience with data governance, data security, and compliance practices in Azure and other cloud platforms.
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Ll work on everything from customer-facing web applications using cutting-edge open source frameworks, to highly-available RESTful services, to back-end Java based systems using the hottest techniques in Big Data. You.
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As a Data Engineer, you will be a part of a small but growing team of hardworking people responsible to lead the Data platform initiatives at Clover and establish a scalable and streamlined Data ops culture across all Clover engineering teams.
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