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The Data Architect will be held accountable for the following responsibilities: Define and implement the long-term technology strategy and innovations roadmaps across analytics, data engineering, and data platformsCreate standards, design patterns, and best practices for ETL development in an enterprise data warehouse environment.
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3+ years of experience in batch and streaming ETL using Spark, Python, Scala, Snowflake, or Databricks for Data Engineering or Machine Learning workloads. We are looking for a Senior Data engineer.
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5+ years of experience in data analysis or related fields such as Data Scientist, Computational Biologist, or. MS/PhD in Electrical Engineering, Statistics, Bioinformatics, Computational Biology, Computer Science, Mathematics, or equivalent practical experience.
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Solid understanding of data engineering concepts, including data modeling, data processing pipelines, and big data technologies (e.g., Hadoop, Spark, Kafka). Experience working with relational and NoSQL databases, as well as cloud-based data storage solutions (e.g., AWS S3, Google Cloud Storage, Azure Blob Storage.
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Proficient in developing code utilizing Azure, Hadoop, Databricks, Control M, Spark, SQL Server, Big Data Analytics, Azure Services, Unix scripts, Java, and Oracle. As a Big Data Architect, you will be responsible for designing and implementing large-scale data processing systems, optimizing data workflows, and integrating new technologies to support our growing data needs.
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You Have: 3+ years of experience in batch and streaming ETL using Spark, Python, Scala, Snowflake, or Databricks for Data Engineering or Machine Learning workloads. You will report to the Mgr, Product Engineering You will: Design and implement technical solutions and processes to ensure data reliability and accuracy.
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Work as the liaison between Engineering, technology and procurement teams on development and optimization of product data across multiple systems / processes with focus on data quality, integrity and governance.
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Required Qualification: Proficient in developing code utilizing Azure, Hadoop, Databricks, Control M, Spark, SQL Server, Big Data Analytics, Azure Services, Unix scripts, Java, and Oracle.
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Ability to work with IT and Data Engineering teams to help embed analytic outputs in business processes. Exposure to cloud platforms and big data systems such as Hadoop HDFS, Hive is a plus.
$200ExpandApply NowActive JobUpdated 2 days ago - UpvoteDownvoteShare Job
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Collaborate with product managers, designers and data analysts to help define the team s scope of work for both product-led and engineering-led initiativesParticipate in a one-week on-call rotation to support our services.
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Desing Develop release and support, Cloud Native applications running on Containers Kubernetes and Docker within AWS.
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Software Engineer responsible of designing, building and testing Risk application interface for quantitative models. Measure and improve existing software efficiency, memory footprint, and computational efficiency.
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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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Engineering at Early Warning (EWS) is a blend of teams organized around many different platforms, capabilities and products that are brought together to power core capabilities at the biggest banks in America – this includes ubiquitous products like Zelle and Paze. These capabilities are typically provided behind a customer-facing API or integration point which enables the EWS teams to innovate aggressively where big wins can be found.
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Proficient with software used for data mining, statistical analysis, and data visualization (SAS, SQL, R, SPSS, Qlik, Power BI, Tableau, etc.) in order to construct a robust, accurate, 360-view data environment that is unique to each client•Demonstrated performance excellence in one or more of the following computer languages: SQL, SAS, R, Python•Employing techniques such as a case-control study, regression analyses, principal component analyses, clustering exercises, propensity scoring, classification, ROI calculation, etc.
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big data software engineering jobs Title: big data engineer Company: Synopsys in Chicago, IL
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