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Experience working with large datasets and big data technologies, preferably cloud-based (e.g., Redshift, Databricks, Azure SQL Data Warehouse, MongoDB). Design and implement data integration solutions, leveraging ETL/ELT tools such as Apache Spark, Informatica PowerCenter/BDM, and SSIS.
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1+ years experience with GCP and Azure Cloud Big Data tools (PowerBI/DataLake/ Azure Databricks) They will create, tune, maintain, and build reporting Big Data platforms that drive business.
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Familiarity with big data technologies, such as Amazon Redshift, Google BigQuery or Snowflake. Knowledge of machine learning algorithms and data analysis techniques for optimizing ad targeting and performance.
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Experience with big data technologies and platforms, such as Apache Hadoop, Apache Spark, Apache Kafka, and distributed data processing frameworks. Familiarity with cloud platforms like AWS, Azure, or Google Cloud, including services for data storage, data processing, and orchestration (e.g., AWS S3, AWS Glue, Azure Data Factory.
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Knowledge of some of the main components of Azure Analytics: Azure Data Processing Technologies (DataFactory, Databricks), Azure Big Data Technologies, Databricks, Synapse. The ideal candidate will have extensive Microsoft/Azure data services and Databricks technology experience.
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Azure Integration: Work with Azure services such as Azure Data Factory, Azure Databricks, and Azure SQL Database for data integration, processing, and storage. We are seeking a skilled Data Engineer with extensive experience in DBT, Snowflake, and Azure, along with proficiency in Python and SQL. The ideal candidate will have a strong understanding of data modeling principles and a proven track record of developing robust data pipelines and architectures.
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As part of NTT DATA, a $30 billion trusted global innovator with a combined global reach of over 80 countries, we help clients transform through business and technology consulting, industry and digital solutions, applications development and management, managed edge-to-cloud infrastructure services, BPO, systems integration and global data centers.
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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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Our Adaptive MDR solution, powered by Resolution Intelligence Cloud technology, leverages artificial intelligence and big data to deliver customized experiences and data-driven results for every customer.
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Develop and maintain robust, scalable, and efficient data pipelines using Snowflake, SQL, Tableau, and DBT. Knowledge of Databricks is a big plus! Stay up-to-date with industry best practices and technologies in analytics and data engineering.
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The CENTROID Data Science team develops intelligent solutions to make highly visible and big impact decisions in Network transformation at Walmart. 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.
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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 modelling platforms such as Azure AutoML, SageMaker, DataBricks, DataRobot, and H2O.ai.
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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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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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The Data Warehouse Architect will also evaluate and provide input on infrastructure components such as software, hardware, database management systems, and networking capabilities. · Assess and cultivate long-term strategic goals for data warehousing in conjunction with IT architect(s), data users, department managers, clients, and other key stakeholders.
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big data jobs Title: technology lead Company: Inc in Irving, TX
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