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Familiarity with Big Data technology in cloud and on-premises environments: Hadoop, HDFS, Spark, NoSQL Databases, Hive, MongoDB, Airflow, Kafka, AWS, Azure, Dockers or Snowflake. We are a premier IT consulting firm specializing in delivering top-tier Big Data solutions to companies across various sectors such as.
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5+ years of experience designing, building, and supporting real-time and batch data pipeline and analytical solutions with Hadoop (Hive, Kafka, Spark, Spark Streaming, HBase) and Teradata, ETL tools like Informatica, Talend, Data Fusion, Python/Java, Oracle/Exadata.
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O Big Data technologies: Kafka, Apache Spark, Hadoop. cts as a source of technical Architect; serves as a role model for others in displaying functional capability and continually acquiring new skills.
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Big data technologies like Hadoop (Hortwonworks, Cloudera, Azure HDInsight, Amazon EMR), Spark, Kafka, Elasticsearch and others; Advanced analytics development experience with R, Python a plus.
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Hands-on experience with big data technologies such as Hadoop, Spark, Kafka, and distributed computing frameworks. Relevant certifications (e.g., Azure, databricks, snowflake) would be a plus.
$75 - $90 an hourExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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Experience in Hadoop, HDFS, Hive, Presto, REST/SOAP API, Spark2, Airflow is a plus. 6+ years’ experience working within the AWS Big Data/Hadoop Ecosystem (EMR, Glue and Athena.
$140,000 - $180,000 a yearFull-timeExpandApply NowActive JobUpdated 17 days ago - UpvoteDownvoteShare Job
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Must be strong in: J2EE, Spring Boot, Micro Services, Angular, MongoDB, KAFKA, Junit, with competencies in: Java Script, SOAP, MQ Series, ECLIPSE, Tomcat Application Server, Unix, Gradle, NOSQL Industry standard Java certification a plus.
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7+ years as a lead data engineer in developing & managing data pipelines using ETL/ELT tools and data visualization using business intelligence. 3+ years as a Data Engineering Manager managing multiple Agile Squads/Teams that works on multiple projects in an Agile environment.
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Big Data Architecture, Cloud Data Platforms Architecture (Azure, Databricks, Snowflake), In-house Big Data Platforms (Hadoop, Teradata, Exadata) This role provides you with a broad platform to build partnerships with business and risk counterparts, a vantage point to explore end-to-end data ecosystems and technologies, and ability to co-develop data solutions for GRM that drive the greatest value across the organization.
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Experience in data storage (ADL/S3) and big data processing (Kafka, Hive, Databricks, etc.) Senior Business Data Architect holds a crucial role within the Data & Analytics Strategy and Innovation function, steering the development and implementation of holistic data strategies to underpin the organization’s business operations and decision-making endeavors.
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Agile Scrum, Jira, Bitbucket, Jenkins, Splunk, Kafka, Hadoop, Reports, Selenium, Microservices and APIs, Deployment automation, unit test automation, CI/CD tools. Experience in Designing and Implementing PEGA Enterprise Class Rules, Flows, Activities, Repots, Correspondence, Case Management and Integrations, Data Pages, Agents, UI design, Dashboards, Reports, Troubleshooting and debugging.
ExpandApply NowActive JobUpdated 3 days ago - UpvoteDownvoteShare Job
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Big Data Analytical Platforms: Experience with big data technologies like Synapse Analytics, Microsoft Fabric, Hadoop/hive, Greenplum, and Databricks etc. Strong understanding of big data technologies such as Synapse Analytics, Microsoft Fabric, Hadoop/hive, Greenplum, and Databricks etc.
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Strong experience with cloud platforms such as AWS, Azure, GCP and analytical data stores: Data Lake, Snowflake, Redshift, Hadoop. 10+ years of experience in data modeling and data architecture including at least 5 years in a leadership or management role with strong understanding of data architecture and data governance principles and practices.
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Expertise in various phases of project life cycles Design Analysis Implementation and testing ETL Tools Ab initio, GDE, Ab Initio Co Op Databases, Teradata Oracle 10g, 11g, Exadata, My SQL, SQL Server 2008, DB2 Cosmos DB, Hadoop, Hive, Snowflake Other tools Autosys Control, M Client ALM, Jenkins, IBM Udeploy GitHub WinSCP, MSVisio, AWS Services, Service Now, AUTOMIC AROW, Airflow Windows, Powershell Python, IDLE, Kafka, GCP, Google Cloud Platform, Azure Big Data Technologies, Hadoop, Spark.
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Under DSM Executives leadership, the SCI team will develop a holistic vision on how best to structure data sourcing and data quality control strategy for GRM so it can unlock business value.
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