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Strong Knowledge in Big Data Technologies, PySpark, thorough in one or more programming language like Python. We are seeking a highly experienced Senior Data Engineer with a deep understanding of PySpark using Databricks or AWS Glue or AWS EMR and cloud-based databases such as Snowflake.
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We are looking for a Senior Data Engineer to help us continue to build the next evolution of our data platform in a scalable, performant, and customer-centric architecture. Primary responsibilities for a Senior Data Engineer Collaborate with Product Managers, Designers, Engineers, Data Scientists and Data Analysts to take ideas from concept to production at scale.
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Latitude specializes in providing highly skilled former in-house counsel and Big Law attorneys for flexible contract engagements and permanent positions in dozens of practice areas, including commercial contracting, data privacy, M&A, employment, litigation, and more.
$150,000 - $400,000 a yearFull-timeExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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We are looking for a senior data solutions engineer with extensive experience in the big data and data warehouse ecosystems. In addition, be a key contributor in delivering critical business features with a passion for big data technologies.
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Good command of database technology and query languages (SQL) and non-relational DB and other Big Data technology, including efficient storage and serialization protocols (eg Parquet, Avro, Protocol Buffers.
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This director will need hands-on experience with Java, DevOps, CICD, AWS, Containers, terraform, Etc. Responsibilities: Develop and maintain software and environments used to implement and test systems for pricing, margin risk and stress testing of financial products and derivatives.
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Own reference data and investment characteristics of multiple security types while supporting Portfolio Management, Quantitative Research, Trading, and other Firm constituencies. The Data Management Analyst works closely with personnel in Investment Management, Performance Analytics, Securities Operations, IT and other groups and clients, as needed.
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The team tackles problems of massive scale, with a critical data footprint that has bottomline business impact, resiliency & availability requiring the best techniques within Big Data Analytics and Machine Learning, all while providing a superior analyst experience on our tools.
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Data Gathering, Preparation, and Governance : Oversee design and build out of appropriate data governance to ensure that data is complete, consistent, correct, accurate, and timely for internal testing and future submission to the US Federal Reserve Bank; oversee determination, design, and implementation of CCAR production infrastructure, data, and technology needs (e.g. modeling data, model production environment, regulatory reporting.
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The Data Protection Product Compliance Specialist reports to the Sr. Privacy Counsel. Work with Privacy Counsel to advise product teams on preparation of asset lists, data inventories, data flow mapping, privacy questionnaires and records of processing utilizing OneTrust privacy management platform.
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Familiarity with Big Data is preferred. Propose new database architecture and support data migration from an existing Legacy system to a new structureCreate source-to-target mapping documents to transform the source data into the target warehouse and test final transformations.
$87,000 - $115,500 a yearExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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McDonald's is in search of a Data Engineer with a strong background in DevOps engineering. Oversee the deployment, scaling, and management of data analytics platforms such as Talend, Microstrategy, Tableau, and Alteryx.
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Considerations include variety (structured, unstructured), volume (includes big data), data quality (cleaning and validation of the data) and velocity (batch, stream). Data Science tools like Knime, Dataiku, AWS SageMaker, statistical languages, and packages, e.g., R, Python, Julia, SAS, data visualization tools and techniques, e.g., Tableau, ggplot, matplotlib, R/Shiny, Qlik, data manipulation tools such as SQL, Spark, PySpark and Hive, cloud environments like Azure and AWS, deep learning tools such as Tensorflow, Keras and PyTorch.
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Drive the Kraft Heinz Culture and Values; credible partner in driving big cultural initiatives such as Management by Objectives (MBOs), Continuous Improvement and process mapping, as well as ensuring Meritocracy happens at all levels of the organization.
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Proficiency in data technologies, such as relational databases, data warehousing, big data platforms (e.g., Hadoop, Spark), data streaming (e.g., Kafka), and cloud services (e.g., AWS, GCP, Azure.
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big data jobs Title: devops engineer Company: Optello in Chicago, IL
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