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Manage and optimize Apache Spark pools for high-performance data processing tasks. Minimum 3 years’ experience working with Cloud technologies such as Synapse pipelines, Azure Data Factory (ADF), ADLS, Azure Databricks, Spark, Azure Synapse, and other modern data ETL/ELT technologies.
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Your role as a Data Engineer: In this role you will be responsible for designing, developing, and maintaining data pipelines in support of data management functions such as data engineering, data integration and data quality and governance activities.
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Databricks - cloud-based platform built on Apache Spark that provides a collaborative environment for big data processing and analytics. The ideal candidate will have experience with Python, Data Engineering, AWS, and databricks.
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Strong understanding of data engineering concepts and experience with tools such as SQL, NoSQL databases, and data processing frameworks (, Apache Spark). Knowledge of IBM Master Data Management (MDM) implementation.
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ResponsibilitiesYou will assist with on-call rotations as a Live-Ops Incident Commander to help categorize and track real time data incidents, loop in engineering resources as needed to ensure a timely resolution to data issues.
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Lead the processing and analysis of laser scanning data, ensuring accuracy and completeness of results. Proficiency in laser scanning processing software and techniques. The company provides civil and structural engineering, land surveying, construction inspection/management, site safety and special inspection services.
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Hands on experience in data engineering desired with extensive knowledge of SQL and PySpark, on Databricks Platform. Work with an agile team to deliver and evolve data engineering & services.
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Advanced knowledge of cloud computing technologies such as: Apache Spark, Azure Data Factory, Azure DevOps, Azure ML (Machine Learning), Hadoop, Microsoft Azure, Databricks, AWS, Google Cloud.
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Commercial Card Software Engineering, Vice President page is loaded. Bachelor’s or Master’s degree in Computer Science, Software Engineering, or related field. Participate in all phases of software engineering life cycle and troubleshoot technical problems as needed.
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5+ years of experience in data engineering with Databricks and Spark. Design, develop, and maintain data pipelines using Databricks and Spark, and other cloud technologies as needed.
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We provide essential intelligence for Financial Services, Real Estate and Insurance industriesThe Impact: The FIG Data Engineering team will be responsible for implementing & maintaining services and/or tools to support existing feed systems which allows users to consume FIG datasets and make FIG data available to a data fabric for wider consumption and processing within the company.
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Leverage a broad set of modern technologies – including Python, R, and Spark – to analyze and gain insights within large data sets. Master’s degree in Data Science, Statistics, Mathematics, Computer Science, Engineering or another quantitative field, or related field, or the equivalent combination of education, training and experience.
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Familiarity with additional transformation platforms like Apache Spark and Beam. BS in engineering or data related field. Day to day youll be building modeling data to feed analytical reports and data science models, optimizing and creating new ETL pipelines, or building data models in Looker or Qlik Sense.
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The ideal candidate will have a deep understanding of Scala, data pipelines, Apache Spark, and Azure ML, with a proven track record of delivering high-quality software solutions.
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Data Security Procurement group, you will be responsible for establishing and executing sourcing strategies and plans for our Cyber Defense & Engineering + Information Technology department.
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software engineering data processing apache spark jobs Title: engineer in New York
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