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Norfolk Southern Corporation is currently seeking a Big Data Engineer with an affinity for working with others to create successful solutions. 3+ years of Big Data tools like Hadoop, Spark, Spark SQL, Kafka, Sqoop, Hive, S3, HDFS.
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Norfolk Southern Corporation is currently seeking a Senior Big Data Engineer with an affinity for working with others to create successful solutions. Senior Big Data Engineer.
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As a Sr. Big Data Engineer, you will work with a variety of talented teammates and be a driving force in technical initiatives that will accelerate analytics at Client. Big Data Engineer.
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Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and (GCP, AWS, Azure, Snowflake) ‘big data’ technologies.
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We are interested in a variety of topics including data visualization and interactivity, applied machine learning and AI, AI bias and trust, big graphs, natural language processing, data mining, big data management, and heterogenous data analytics.
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We are interested in a variety of topics including large-scale distributed systems, stream processing, edge computing, applied machine learning and AI, big graphs, natural language processing, big data management, and heterogenous data analytics.
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Advanced experience in SQL in big data warehouse systems such as Snowflake, BigQuery, Databricks, etc. Internal knowledge of open source or related big data technologies. What you’ll bring to Circle:For Senior Data Engineer (III) 4+ years of professional data engineering experience.
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Strong experience with Hadoop, Impala, Pig, Hive, YARN, and other big data technologies. The Data Warehouse Engineer is a key new role to the Reibus team. Data Warehouse Engineer.
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Google Cloud Platform Data Engineer. Design, develop and deliver data integration/data extraction solutions using IBM DataStage or other ETL tools and Data Warehouse platforms like Teradata, BigQuery.
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Work with big data technologies like Azure Databricks, Apache Spark & Palantir. We are actively seeking a senior data engineer with Generative AI experience who embodies energy and passion.
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Experience working with big data distributed programming languages, and ecosystems: 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 (Azure AutoML, SageMaker, DataBricks, DataRobot and H2O.ai.
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Hands-on experience in testing and validating ETL pipelines with knowledge of big data frameworks and architectures, including AWS, EMR, Spark, Delta.io, Iceberg, Athena, Git, and DevOps.
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Find even more open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general - ordered by popularity of job title or skills, toolset and products used - below.
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Delivery experience in Data Engineering with Google Cloud Platform including Big Query, Dataflow, Cloud Data Fusion, Cloud Composer, Dataproc, Cloud Pubsub, Cloud Function etc. Propose, own initiatives and demonstrate though leadership that improve the efficiency and productivity of the data science Center of Excellence.
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Android Development, iOS Development, Data Science, Cyber Security, Big Data, Exchange Services, Career Development, Data Engineering, Managed Services, Consulting Services, Business Development, and IT Resources.
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big data jobs Title: devops engineer Company: Crowdstrike in Atlanta, GA
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Job Rejection Email Response with Examples
Glassdoor estimates that, on average, there are about 250 applicants for every job vacancy out there. If you’ve ever applied for a job, the odds are that you’ve received the dreaded job rejection email.
Structured vs Unstructured Interviews
The goal of an interview is to evaluate candidates based on their skills, personality, and knowledge. You want to choose the BEST candidate from your candidate pool, so the interview is something you can't mess up. As you begin planning your interview process, one of the major decisions you'll face is whether the interview should be a structured vs unstructured interview. So let's take a dive into the differences and sort out which circumstances warrant which interview process.
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