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Hands-on evaluation and testing of tools and technologies, including Databricks and Azure , to support data platform management, data extraction, UI/UX presentation, and generative AI. Job Title : Data Engineer (Databricks Platform Modernization.
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Experience with the Azure Services and Data components: Container based solutions, Microservices, Streaming Solutions, Python & Spark Compute, Spark SQL, Azure Integration services, and ingestion tools such as ADF, Snowflake, ADL, and GenAI Cognitive capabilities.
ExpandApply NowActive JobUpdated 18 days ago - UpvoteDownvoteShare Job
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Minimum of 5 years of hands-on skills in Python, Apache Spark, Hive, Cassandra, Snowflake, Elastic, Lucene, DataBricks, Hadoop, Redshift, Scala, Java, or other relevant technologies in data engineering.
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Experience building data visuals and/or dashboards using tools including, but not limited to, Tableau, Qlik Sense, Qlik View, Power BI, etc. Experience using platforms such as Databricks for data analytics, processing, and transformation.
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Collaborating amongst team members across several geographies, our Cloud practitioners engineer cloud-based analytics solutions on AWS, Azure, Databricks, GCP, Snowflake, Oracle, Informatica Cloud and a combination of native cloud technologies, including computing at edge and curating data-in-motion.
$119,025 - $198,375 a yearFull-timeExpandUpdated 15 days ago - UpvoteDownvoteShare Job
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Strong fluency in Python and SQL, experience with Tensorflow, PyTorch, Airflow and data warehouse. We need a strong data scientist leader to manage our ML & data science research & development and evolve the services that make up the backbone of Xometry’s business.
Full-timeExpandApply NowActive JobUpdated 2 days ago - UpvoteDownvoteShare Job
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Hands-on experience with big data technologies and cloud (Databricks / Spark, Azure/AWS/GCP). Excellent understanding of data mining, predictive modeling, and data visualization.
$65,500 - $108,000Full-timeExpandApply NowActive JobUpdated 2 days ago - UpvoteDownvoteShare Job
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RWE Analytics: Utilize advanced analytical techniques to analyze large-scale clinical data sets and derive meaningful insights that contribute to evidence generation for regulatory submissions, market access, and post-market surveillance.
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Utilize programming languages like Java, Scala, Python and Open Source RDBMS and NoSQL databases and Cloud based data warehousing services such as Redshift and Snowflake. 4+ years experience with Distributed data/computing tools (MapReduce, Hadoop, Hive, EMR, Kafka, Spark, Gurobi, or MySQL.
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These include, but are not limited to 1) the establishing of a Production environment in Databricks, 2) the orchestration of Unity Catalog for future state and scalability of data, 3) contextualized MLops/MLflow expertise and implementation, 4) additional silver and gold layer transformations relevant to business needs for data science, BI tools, Web App integration, etc.
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Strong proficiency in computational biology, including genomics, transcriptomics, and proteomics data analysis. Utilize expertise in computational biology, machine learning, and bioinformatics to develop and optimize algorithms and models for the analysis of high-dimensional biological data.
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New York City (Hybrid On-Site): $201,400 - $229,900 for Lead Data Engineer. As a Capital One Lead Data Engineer, you’ll have the opportunity to be on the forefront of driving a major transformation within Capital One.
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The Chief Information Security Officer reports to the Executive Vice President, Data Strategy and Chief Information Officer for the Health System. Reporting to Executive Vice President for Data Strategy and Chief Information Officer, they will act as a focus and resource for information security matters.
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The Statistical Analyst A will use standard SAS and/or Stata to create analytic datasets from clinical trials, health care claims, electronic medical records, and surveys; to construct and standardize analytical variables through data integration and data manipulation; to provide descriptive and analytic reports; and to perform statistical analyses.
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We are responsible for crafting the developer experience for Google Cloud Platform (GCP) developers in the Data Analytics space, including BigQuery, Bigtable, and others. Solid understanding of cloud services like Azure/AWS/GCP, native controls, security center, DDOS protection, cloud firewalls, CASB, express route, cloud data storage, cloud storage, Kubernetes, data sharing related technologies, NetApp, Site recovery, CDN, MS defender, MS Sentinel, AWS EC2, AWS Guard, AWS KMS, Cloud Watch, Lambda, cloud containers, etc.
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data job in Philadelphia, PA
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