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Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using Informatica, Python, SQL and AWS ‘big data’ technologies.
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We do all this with an exceptional group of software engineers, data scientists, SRE/DevOps engineers, and managers. Proficient in best practices and enforcement for data security and data governance.
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Part of a team building out a comprehensive GRC (governance, risk, and compliance) program on the software platform, Archer from RSA (Windows & SQL Server). - Experience in one or more of the following disciplines preferred: big data technologies and distributions, metadata management products, commercial ETL tools, Bi and reporting tools, messaging systems, data warehousing, Java (language and run time environment), major version control systems, continuous integration/delivery tools, infrastructure automation and virtualization tools, major cloud, or rest API design and development.
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4+ years with Big Data Hadoop cluster (HDFS, Yarn, Hive, MapReduce frameworks), Spark, AWS EMR. Skilled in documentation and database reporting for the purposes of analysis, data discovery, and decision-making with the use of relevant software such as Crystal Reports, Excel, or SSRS.
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Microsoft's Azure Data engineering team is leading the transformation of analytics in the world of data with products like databases, data integration, big data analytics, messaging & real-time analytics, and business intelligence.
$94,300 - $198,600 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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Performance Optimization: Optimize data processing and query performance using technologies such as data proc, gcs, and Big Query, while ensuring adherence to data governance SLAs.
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Big Data Software Engineer III. Ensuring industry best practices around data pipelines, metadata management, data quality, data governance, and data privacy.
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What You’ll Do: As a Senior Software Engineer , you will be responsible for working on projects that support and extend the full stack of the TRSS solutions suite to deliver global data using advanced search, big data ingestion and analytical processing using tools like MongoDB, Elastic, and Kafka as well as building leading edge web applications.
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Principal Big Data Software Engineer - Streaming Infrastructure. Principal Full Stack Software Engineer - Engineering Efficiency Service Management. in software engineering, data analysis, and/or quantitative risk assessment is a plus.
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Senior Software Engineer - Big Data Warehouse and Metadata Platform Services. Drive and deliver the ongoing product vision of intelligent big data warehouse and centralized data governance platform.
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DCS’s Infoscitex Sector is seeking an experienced Software Engineer to support development of new sensor data processing/management technologies and associated big data infrastructure leveraging data governance and data standards initiatives.
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As a Staff engineer in the Core Metrics team, you will have the opportunity to work on the design and implementation of big data systems, working with petabytes of data and billions of transactions in real-time.
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Experience working with big data (engineering / processing) and data migration. Database Query Engine, Data Infrastructure, Data Pipelines, Data Platform, Database Security, Data Governance, Data Sharing, FoundationDB, Manageability, Metadata, Service Runtime, Snowhouse Foundation, Storage and ML Engineering.
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Strong expertise in the big data ecosystem, including tools like Kafka, Spark, Apache Iceberg, Airflow, S3, data modeling, data warehouses, OLAP databases, etc. Champion data governance best practices, establishing and enforcing data processing principles, design patterns, and practices.
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As a member of the Data Platform Engineering team, you own the core Big Data/ML platform, data ingestion, processing and serving, ETL/ELT pipelines, data governance and security compliances, data analytics and visualization tooling, data modeling and data warehouse that powers our Product, Engineering, Analytics, and Data Science teams for experimentation, operational excellence, and actionable insights, so as to fuel and accelerate business growth.
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