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Hadoop Admin Ops / SRE role supporting Platforms built around Big Data Technologies (Hadoop, Spark, Kafka, Impala, Hbase, Docker-Container, Ansible and many more). Expert level knowledge of Cloudera Hadoop components such as HDFS, Sentry, HBase, Kafka, Impala, SOLR, Hue, Spark, Hive, YARN, ZooKeeper and Postgres.
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Technical Proficiency: Expertise in SQL and programming languages such as Python; familiarity with big data technologies like Apache Hadoop, Spark, and Kafka. Professional Experience: At least 5 years of experience in data engineering, with a strong focus on data integration and pipeline construction in cloud environments and enterprise data warehouses like Snowflake.
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Advanced Analytics - Applied Econometrics, Advanced Calculus, Statistical Methods, Data Visualization, Decision Analytics & Optimization, ML, Big Data, Social Network Analytics. Techniques: Statistical Analysis, Visualization, Optimization, Machine Learning, Big Data, Data Warehouse, NLP.
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Analytics Tools: Excel, Tableau, AWS, BigQuery, NoSQL,Hadoop, Spark, Airflow, Gurobi, JIRA, Stata, Git. Certificate in business analytics, data mining, or statistical analysis, Statistical programming languages (for example, SAS, R.
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This architecture includes an Databricks, Microsoft Azure platform tools (including Data Lake, Synapse), Apache platform tools (including Hadoop, Hive, Impala, Spark, Sedona, Airflow) and data pipeline/ETL development tools (including Streamsets, Apache NiFi, Azure Data Factory.
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Languages: R, Python (Pandas, Seaborn, Scikit-learn), SQL,Hive, Pig, Impala, Sqoop, Kafka, VBA, Shell. Drive the adoption of data science-driven mechanisms and machine learning models to continuously evaluate and improve catalog data quality.
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3+ years experience with Big Data technologies, such asApache Hadoop, Hive or Spark, Databricks and/or Snowflake. Experience with Data Management methodologies and practices such as data warehousing, data integration (ETL/ELT), visualizations, metadata management, data security, data governance, data quality and analytics.
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Big Data Expertise : 3+ years of hands-on experience with major Big Data technologies and frameworks, including Spark, Hive, ZooKeeper, HDFS, Presto, Hadoop, MapReduce, Tensorflow, and more.
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5+ years working experience with key open source big-data projects as a contributor or committer including Apache Spark, Apache Flink, Trino, Apache Kafka, Apache Hive, Apache Arrow, Apache Hadoop, Delta Lake, Apache Iceberg.
$268,000 - $414,000 a yearFull-timeExpandApply NowActive JobUpdated 5 months ago - UpvoteDownvoteShare Job
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In-depth knowledge of big data technologies such as Hadoop, Spark, Kafka, and cloud platforms such as AWS, Azure, GCP, Snowflake, Databricks, etc. Professional certifications in cloud computing (e.g., AWS Certified Solutions Architect, Microsoft Certified Azure Solutions Architect, Azure Data Engineer, SnowPro Core) and/or big data technologies.
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Hands-on development experience with Design and Architecture of big data frameworks/tools: Azure Data Lake, Snowflake, Azure Data Bricks. Solid understanding of Snowflake computing, including its integration with Azure Data Lake, utilizing ADLS as a source for data processing.
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Experienced with big data processing technologies (Spark, Storm, Kafka, Flume, Pig, Hive, Sqoop, Hadoop/MapReduce, etc. Experienced with development and modeling for columnar storage and massively parallel processing data warehouses (Hadoop, Snowflake, Redshift) with a keen sense to optimize for scalability, availability, security, cost, and performance.
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Expertise in Cloudera Big Data Technologies, including Cloudera Distribution of Hadoop (CDP), Apache Hadoop, Apache Spark, Apache Hive, Apache Impala, and Apache HBase, with hands-on experience in deploying, configuring, and optimizing these technologies for large-scale data processing and analytics.
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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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SKill: Big Data Architect, Cloudera Big Data Tool stack (Hive ,Impala, OoZie), Pyspark, Teradata, Shell Script, Unix programing, Hadoop. Proficiency in Python for advanced data analysis, scripting, automation, and integration with Big Data platforms and ecosystems.
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hadoop kafka big data integration jobs Company: The Friedkin Group
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