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Familiarity/experience with various data formats including database specific (Oracle, SQL Server, DB2, Quickbase), text formats(CSV, XML) and Binary(Parquet, AVRO) Familiarity/experience with data integration and data pipeline tools (e.g., Informatica, Synapse, Apache NiFi, Apache Airflow.
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Experience with various data formats including database specific (Oracle, SQL, Postgres, DB2), text formats (CSV, XML) and Binary (Parquet, AVRO) Strong experience with Microsoft Azure tools such as Azure Data Factory, Synapse, SQL Database, Data Lake Storage Gen2, Blob Storage.
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The candidate should have strong programming skills, proficiency in SQL and scripting languages, and experience with AWS data services such as S3, Glue, Redshift, and Athena. Responsibilities include designing, developing, and maintaining ETL pipelines, implementing data integration solutions on AWS cloud services, and optimizing data processing workflows.
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Microsoft builds a world-class SQL engine with decades of innovation that is used in SQL Server, Azure SQL Database, and our cloud analytics scale-out SQL offering Azure Synapse offering data warehouses storing hundreds of terabytes of data.
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Perform installation, configuration management, capacity planning, license management, data integration, data transformation, field extraction, event parsing, data preview, and application management of Splunk platform.
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Skills: Oracle Application Express (APEX), WebLogic, IIS, Oracle, SQL Server, OBIEE/Oracle Analytics, Oracle Data Visualization, D3, MS Access, SQL, Agile Software Development, Software Development Life Cycle.
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Knowledge and expertise in JEE, AWS, SOA, web development, web services, XML, JSON, DHTML, and Oracle 11G (or higher)/SQL Server. Implement data integration solutions on AWS cloud services.
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Interface with the ABMS performers and facilitate data integration Program Management Dashboards, Systems Engineering and Development Dashboards, Network Operations Dashboards. Experience as a SQL Server DBA.
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Experience using enterprise database platforms (Oracle, IBM, SAP HANA, SQL Server, PostgreSQL) and cloud platforms. Experience developing and automating extraction, transform, and load (ETL) processes including using enterprise data integration tools.
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Demonstrated ability to use and integrate database and data visualization tools. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.
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Develop and implement data migration and integration processes. Familiarity with database management tools and systems (e.g., Microsoft SQL Server, Oracle, MySQL). You will work closely with cross-functional teams to design and optimize databases, write efficient SQL queries, and ensure data integrity and security.
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MS SQL Server 2008 R2; with other commercial reporting and analytic tools like Tableau, Power BI, Crystal reports, etc. REQUIRED SKILLS AND EXPERIENCE: Ability to design, install, implement, and administer SQL Server databases and servers in the DoD environment to include MS SQL Server 2016 Ability to implement MS SSRS systems and develop and deploy reports.
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Proficiency in Informatica PowerCenter for ETL workflows, transformations, and data integration tasks. Ability to design, develop, and maintain ETL pipelines and data integration solutions.
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Your role will involve crafting and maintaining ETL pipelines, implementing data integration solutions on AWS cloud services, and fine-tuning data processing workflows. Proficiency in communication and expertise in JEE, AWS, SOA, web development, web services, XML, JSON, DHTML, and Oracle 11G (or higher)/SQL Server.
$65 - $75 an hourFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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This includes standing up, maintaining, and decommissioning SQL Server instances according to industry best-practices and logically integrating the data housed within the firm’s enterprise applications into both new and existing data structures.
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