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Implementation and tuning experience in the Big Data Ecosystem, (such as EMR, Hadoop, Spark, R, Presto, Hive), AWS Solutions Architect, AWS Developer, or AWS Certified Big Data – Specialty (Data Analytics Specialty.
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Experience leading the design/implementation of configuration driven, scalable, reliable services and big data workflows/pipelines using EMR, Kafka, Spark, Hive, Airflow or equivalents.
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4+ years of experience working with Big Data Technologies such as Apache Spark, ● 2+ years of experience with Databricks capabilities related to data engineering. ● Preferred: Databricks Certified Data Engineer Associate/Professional Certification.
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Experience with Snowflake/BigQuery, Google Dataproc/Databricks or any big data frameworks on Spark. Experience with real-time and streaming technology (i.e. Azure Event Hubs, Azure Functions, Pub/Sub, Kafka, Spark Streaming etc.
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Areas of focus will include but not be limited to blockchain, cryptocurrency, artificial intelligence, machine learning, cybersecurity, data privacy, virtual reality / augmented reality, big data/predictive analytics, and social platforms.
$195,000 a yearFull-timeExpandApply NowActive JobUpdated 29 days ago - UpvoteDownvoteShare Job
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Data Platforms – Hadoop, Spark, Oracle, Exadata, SQL Server, DB2, MongoDB, Teradata, Splunk. Hands on experience with data modeling tools (SAP PowerDesigner), database management systems, big data environments and ETL tools.
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More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark, Delta Lake and MLflow.
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Experience building data pipelines - using a variety of different technologies like Azure Data Factory, Databricks, Python & Spark. Hands-on experience designing and deploying large-scale data applications using emerging cloud, big data, SQL and NoSQL solutions.
$201,200 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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Grow into a Big Data professional or Technical Architect role over a period. Designing enterprise data platforms on cloud (Azure/AWS/GCP) including services like ETL pipelines, Data Modeling, Visualization, Data Governance, RDM/MDM, etc.
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3+ years experience with Distributed data/computing tools (MapReduce, Hadoop, Hive, EMR, Kafka, Spark, Gurobi, or MySQL) At least 1 year of experience in big data technologies.
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5+ years of experience in data analysis or related fields such as Data Scientist, Computational Biologist, or Bioinformatics. Perform statistical and subpopulation analysis on sensor and clinical data collected from clinical trials.
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Because we know that heat arises the intersection of complementary forces, our professionals come from myriad disciplines and backgrounds: data, analytics, and insights, content and creative production, communications and strategy, finance and marketing, and sociology, psychology, and other liberal arts disciplines.
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Preferred] Experience with high speed distributed computing frameworks like FLINK, Apache Spark, Kafka Streams, etc. A contributor in developing scalable and resilient hybrid and Cloud-based data solutions supporting critical financial market clearing and risk activities; collaborate with other developers, architects and product owners to support enterprise transformation into a data-driven organization.
$135,000 a yearFull-timeExpandApply NowActive JobUpdated 13 days ago - UpvoteDownvoteShare Job
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Because we know that heat arises at the intersection of complementary forces, our professionals come from myriad disciplines and backgrounds: data, analytics, and insights, content and creative production, communications and strategy, finance and marketing, and sociology, psychology, and other liberal arts disciplines.
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Extensive experience with big data platforms (e.g. Apache Hadoop, Apache Spark, Hive, etc.) Dig in by extracting data and performing segmentation and statistical analyses on large population datasets (using languages such as SQL, R, and Python on Linux and Big data platforms.
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big data apache spark jobs Company: Pfizer in Chicago, CA, Us
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The summer had economists from around the globe embroiled in a debate about a possible recession coming in the next few years (or months). As of October 2022, the U.S. Labor Department data put the current inflation rate at 7.7%. The recent layoffs in the tech industry are just the first of what is soon to be a string of cutbacks by companies looking to save costs. For recruiters, this means freezes in hiring and fewer openings. It will also include the uphill task of finding the best candidates for them from the coming influx of recently laid-off job seekers. Now is probably a good time to brace for tough times in the next few years in the talent acquisition industry. To survive and thrive recruiting in a recession, here are some hard truths you will need to accept.
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Talent acquisition is a multi-stage process where candidates undergo various application steps before getting hired. The unfortunate reality is that it is a labor-intense system, with the hiring manager and recruiter often handling all of the work on their own. Ask any one of them, and you will hear about the overabundance of applications and the demanding task of filtering through them to find the best candidates. The quality of talent suffers under the weight of all that work on one person's hands. It's not easy, but as many companies are starting to realize, there is a better way. The future of talent acquisition lies in collaborative recruiting!