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Strong project experience in Big Data, Cloudera Distribution. experience in Big Data, Cloudera Distribution 7. experience building data pipelines using Hadoop components Sqoop, Hive, Solr.
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Minimum of 10 years of experience in big data, database and data warehouse architecture and delivery. Big Data/analytics/information analysis/database management in the cloud.
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Expert understanding of MS Office, Excel, SQL, or other data visualization tools and big-data analytic techniques for structured and unstructured data. Practical understanding of MS Office, Excel, SQL, and PowerBI or other big-data analytic techniques for structured and unstructured data.
$85,800 - $180,200 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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As a Data Scientist Intern at Big Tech Company, you will be responsible for establishing a data-driven culture of exploitation for our consumer products. Data Scientist Intern | Big Tech Company.
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As a big data engineer at Booz Allen, you’ll implement data engineering activities on some of the most mission-driven projects in the industry. We need an experienced data engineer like you to help our clients find answers in their big data to impact important missions—from fraud detection to cancer research to national intelligence.
$58,400 - $133,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Hands-on experience with big data technologies, including Apache Spark and Databricks Delta Lake. Stay abreast of the latest advancements in Databricks and other relevant technologies to continually enhance data engineering practices.
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Experience with at least 3 of the technologies/tools mentioned here: HAProxy, Kafka, Big Data/ Hadoop, Presto, Spark, Airflow, Pinot, Druid, Opensearch, Gcp, Data Proc. Experience scaling production systems running Big Data tools like Spark, Hadoop, Apache Druid, Looker.
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You likely have experience with a variety of architectures, patterns, and methodologies focused on Analytics Strategy, Data Governance & Master Data Management, Data Architecture(s), Distributed Systems, ETL, Big Data, IoT, Data Visualization and Analytics.
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Experience solving Big Data batch and real-time data processing problems, with large-scale analytics and data processing engines such as Apache Spark and Databricks. Knowledge of Python data science tools, such as SciKit, Numpy, TensorFlow, Jupyter.
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Extensive experience working with large complex data and proficiency in corresponding query/ programming languages such as SAS, R, Python, or SQL plus experience with other big data technologies such as Hadoop.
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Skill - Big Data, Spark, SQL, parkStreaming-Kafka-Python / Scala / Java. Experience in Big Data technologies including Spark, Scala and Kafka. Job Title: Big data Developer.
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2+ years experience on Big data pipelines/DAG tools like Airflow, dbt is required. This role will primarily be responsible for building out our analytics platform on Databricks, using dbt and Python for data transformations.
$90,000 - $144,000 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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Experience working with cloud or on-prem Big Data/MPP analytics platform (i.e. SnowFlake, Netezza, Teradata, AWS Redshift, Google BigQuery, Azure Data Warehouse, or similar). 3+ years' of experience with workflow management engines (i.e. Airflow, Luigi, Prefect, Dagster, digdag.io, Google Cloud Composer, AWS Step Functions, Azure Data Factory, UC4, Control-M.
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Expertise in Python and SQL, with working experience in Apache Spark, Hadoop, Databricks, Snowflake, or other big data systems is preferred. BS, MS, or PhD in Computer Science, Statistics, Applied Mathematics, Data Science, Economics or related quantitative fields.
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Experience with big data technologies (e.g., Databricks, Snowflake) and data visualization tools (e.g., Qlik Sense, D3. Heavy concentration in mathematics, including statistics and programming, business intelligence/analytics, as well as data science tools and research using large data sets.
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big data jobs Company: Feed 8
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How to Increase Job Ad Exposure
In today's competitive job market, writing quality job ads is critical for attracting top talent to your organization. While networking and candidate referrals are prime real estate for finding qualified candidates, nothing beats the tried-and-true method of writing an extraordinary job ad. But while writing a great job ad is the first step, what's more important is increasing visibility. You could have the most detailed, well-written ad on the internet, but if no one sees it, then you are wasting time (and potentially money!). Employers often believe that job boards are the root of the problem, but you can learn how to increase job ad exposure by tweaking a few steps of your recruitment process.