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Proven experience as a Technical Lead with a focus on Databricks and big data technologies on Azure Cloud Platform. Optimize the performance of big data processing tasks and analytics jobs.
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Proficient in Python/R, PyTorch/TensorFlow, SQL, Big Data and cloud technologies. Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch.
$126,000 - $216,000 a yearFull-timeExpandApply NowActive JobUpdated 11 days ago - UpvoteDownvoteShare Job
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Build high-performing data processing frameworks leveraging Google Cloud Platform and utilizing GCP Services like Big Query, Python, Composer, Dataflow, GKE, Pub-Sub, Cloud Monitoring. As a member of the Data and Analytics organization, you will be responsible for designing, building, and maintaining best-in-class data engineering pipelines aimed at driving best-in-class solutions primarily using Cloud platforms like GCP. You will collaborate with cross-functional teams, including data scientists, analysts, business SME’s and software engineers, to ensure the efficient and reliable processing, storage, and retrieval of data.
$72,100 - $144,200 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Experience with multiple large-scale Enterprise Hadoop or Big Data, Data Bricks, Cloudera, HD Insights, or other environments focused on operations, design, capacity planning, cluster setup, security, performance tuning, and monitoring.
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Building data processing pipelines to integrate large datasets from multiple sources and formats, in both streaming and batch mode; Designing and developing data pipelines from ingestion to consumption within big data architecture using Python, Java, SQL etc.
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End-to-end supply chain of data including, but not limited to, AI and Advanced Analytics, Business Intelligence, Cloud enablement, Data Privacy, Data Science, Digital Transformation, Data Governance / Data Management, Enterprise Data Architecture, RPA/Intelligent Automation, Risk and Regulatory Compliance.
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Conduct in-depth risk assessments for Big Technology companies to identify potential risks in the areas of content and activity moderation, consumer data protection, competition, policies and other mechanisms to counter harm, responsible product/service design, data governance and protection and trust and safety and develop and execute controls testing plans, assessing the adequacy and effectiveness of internal controls in mitigating identified risks.
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Strong experience working on Databricks, DBT and data visualization tools like Power BI Strong knowledge of database technologies, ETL processes, cloud platforms, and big data technologies.
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Supermicro® is a Top Tier provider of advanced server, storage, and networking solutions for Data Center, Cloud Computing, Enterprise IT, Hadoop/ Big Data, Hyperscale, HPC and IoT/Embedded customers worldwide.
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The Data Warehouse Architect role involves strategically designing and implementing data warehouses, data marts, and data stores as well as requisite ETL (Extract, Transform, Load) and visualization (reporting) development while ensuring high levels of data availability.
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Oversee the implementation of data processing workflows, analytics, and machine learning models using Databricks. Design and implement scalable and efficient data processing architectures using Databricks.
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Proven experience as a CEO, CIO, CTO, COO, CFO, President, Senior VP who is experienced in running P&L business unit of big US company. \- Proven experience as a CEO, CIO, CTO, COO, CFO, President, Senior VP who is experienced in running P&L business unit of big US company.
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We're hiring a skilled DataBricks Implementation Specialist to design, deploy, and manage DataBricks environments for optimal data processing. Design, deploy, and maintain DataBricks clusters for data processing, analytics, and machine learning.
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Experience working with big data distributed programming languages, and ecosystems such as Spark, Hadoop, MapReduce, Pig, Kafka. Experience with common data science tools such as Python, R, PyTorch, TensorFlow, Keras, NLTK, Spacy, or Neo4j, and a good understanding of modeling platforms such as Azure AutoML, SageMaker, DataBricks, DataRobot, and H2O.ai.
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Experience with big data technologies (eg, Snowflake, Google BigQuery) and cloud computing platforms (eg, AWS, GCP, Azure) Proficient in programming languages such as Python, R, and SQL for data manipulation and analysis.
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big data jobs Title: hadoop consultant Company: Dice in Dallas, TX
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