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Solid experience in building Big Data Pipelines (Batch and NRT) on Hadoop Ecosystem including HDFS, Hive, Spark, Scala, Sqoop, Kafka, NiFi, and real time streaming technologies and host of big data open source stack.
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Ber 3 Jahre Implementierungsfertigkeiten mit Big Data-Technologien wie Spark, Kafka, Hadoop oder Delta Lake. Idealerweise eine erfahrene Person, die mit Big Data-Technologien wie Hadoop, Spark, MPP- und NoSQL-Datenbanken sowie Cloud-Infrastruktur (Azure, AWS oder Google) gut vertraut ist.
ExpandApply NowActive JobUpdated 18 days ago - UpvoteDownvoteShare Job
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Big Data Technologies: Strong knowledge of big data technologies and frameworks, such as Apache Hadoop, Apache Spark, Apache Kafka, Apache Hive, or Apache Flink. Understanding of big data technologies such as Hadoop, Spark, and related ecosystem components (e.g., HDFS, Hive, Pig.
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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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This role requires a deep understanding of big data technologies, particularly Apache Spark, as well as expertise in data engineering and analytics. Proven experience as a Technical Lead with a focus on Databricks and big data technologies.
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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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Data Warehousing: Familiarity with data warehousing concepts and technologies, like Azure Synapse, Amazon Redshift, Google BigQuery, or Snowflake. Familiarity with cloud-based data platforms (e.g., AWS Redshift, Google BigQuery, Azure SQL Data Warehouse) and related services.
$190,000 - $200,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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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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Experience with modern data platforms (Azure Synapse, Databricks, Redshift, Big Query, Snowflake). Utilize programming languages like Java, Pyspark, Python and Open Source RDBMS and NoSQL databases, and Cloud-based data warehousing services such as Redshift and Snowflake.
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Optimize the performance of big data processing tasks and analytics jobs. Oversee the implementation of data processing workflows, analytics, and machine learning models using Databricks.
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Experience with master data (MDM), metadata, and data governance tools. Expertise in ETL/ELT, SQL, and cloud data integration tools (Azure Data Factory, AWS Glue, Informatica.
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Diplômé·e d’études supérieures dans le système d’information, computer sciences, big data (école d’ingénieurs, école spécialisée ou équivalent universitaire), vous justifiez d’au moins 5 ans en Data engineering.
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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. Preferred Qualifications: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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You’ll have the opportunity to work alongside other talented engineers, CTO, and data scientists on cutting-edge big data, search, machine learning and analytics problems. You’ll combine your technical vision, analytical, communication and leadership skills to drive the design, development and implementation of big data systems.
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Responsibilities: •Architect and design big data storage and analytic solutions on Hadoop–based platform, create custom analytic and data mining algorithms to improve performance.
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big data jobs Title: hadoop consultant Company: Iri
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