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1+ year(s) of experience in Cloud data engineering, preferably Google Cloud with Big Query. 3+ years of experience in designing, building, and deploying production-level data pipelines using tools from Hadoop stack (HDFS, Hive, Spark, Streaming, HBase, Kafka, Oozie, NiFi etc.
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Good experience with message driven software patterns (Kafka, MQ) and big data technology ( Hdfs, Hive, Hbase, Spark, Impala, Zeppelin,Jupyter, Cassandra, Elasticsearch, etc.) Experience in building data pipelines using Spark/Glue.
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Familiarity with big data processing frameworks like Apache Spark or Hadoop. Strong proficiency in Azure data services such as Azure SQL Database, Azure Synapse Analytics, Azure Data Lake Storage, Azure Databricks, and Azure Cosmos DB.
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Experience with Big Data Technologies ( i.e., Hadoop, HDFS , MapReduce, Hive, Pig, Spark, etc. Proficient in programming in Python or Java with prior Apache Beam/Spark experience a plus.
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Knowledge of Big Data, data science and statistical analysis skills, e.g. R, Python, machine learning, SAS. Knowledge of analytic tools and platforms, e.g. Tableau, snowflake, Spark, SQL.
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Define data storage and retrieval mechanisms, including multi-tenant data partitioning, indexing, and compression, to optimize performance and cost efficiency. Experience with data governance, data security, and compliance practices in Azure and other cloud platforms.
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Experience with big data technologies (e.g., Hadoop, Spark, Hive) and data visualization tools (e.g., Tableau, Power BI) is a plus. As part of our continued commitment to excellence, we are seeking a talented Data Scientist focusing on data management & data quality.
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Familiarity with big data processing tools (e.g., Hadoop, Spark) is advantageous. Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or a related field.
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Collaborate with senior engineers and data scientists to understand project requirements and develop machine learning models and algorithms. Experience with data preprocessing, feature engineering, and model evaluation techniques.
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Assist in collecting, preprocessing, and analyzing data to uncover patterns and insights. As a Junior Machine Learning Engineer, you will have the opportunity to work on exciting projects, develop your skills, and contribute to the development and implementation of machine learning solutions.
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As a Machine Learning Engineer, you will have the opportunity to work on exciting projects, develop your skills, and contribute to the development and implementation of machine learning solutions. Familiarity with machine learning frameworks and libraries, such as TensorFlow, PyTorch, or sci kit-learn.
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Must Have Technical/Functional Skills •Senior level solution architecture skill for “ Big Data” stack involving rea time processing of very high volume of data (>1B+ records /sec) with minimum latency •Deep knowledge and hands-on development skills Flink ,Spark, Kafka, Python, Cassandra, Apache Druid.
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1+ years experience using Big Data technologies and tools (e.g. Spark, Hadoop, Hive, Cassandra, Druid, Flink, Drill, Trino, NoSQL) Assist with data acquisition, ingestion, and tagging; data exploration and understanding; feature extraction and analysis; data engineering and conditioning; data labeling; and constructing, training, and validating AI/ML Datasets.
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Knowledge in Big data tools like Python, Spark, Hive etc. Expertise in Data analysis & investigation activities. Required Skills: 4+ years of experience in Level-3 Production Support activities with hands on experience in Oracle SQL and PL/SQL, Unix shell scripting, AutoSys, Ab>Initio, Bit Bucket and Service Now.
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Job Title: Sr. Big Data Developer. Job Description : 8+ years of extensive IT experience with multinational clients working in diverse fields of software development lifecycle with experience in Big Data/Hadoop Ecosystem.
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spark big data jobs in Tampa, FL
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