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Experience with data warehouse and big data technologies such as Azure Synapse Analytics, Azure Data Lake Storage, Spark, Kafka, Databricks, and Containers. Implement data processing pipelines using Azure Data Factory, Databricks, Azure Machine Learning, Azure Logic Apps, Azure Function Apps, Azure Kubernetes container and other big data services.
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The Big Data platform supports operational real-time event-based processing and compute applications as well as analytics consumption use cases including machine/deep learning. 10+ years of experience in Hadoop/big data technologies.
ExpandApply NowActive JobUpdated 4 days ago - UpvoteDownvoteShare Job
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Builds & maintains big data pipelines to support advanced analytics and data science solutions. Bachelor's degree and at least 4 years of experience in data engineering OR a Graduate Degree in a technical discipline and at least 2 years of experience in data engineering.
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Experienced with open source big data processing technologies such as Airflow, Hive, Flink, Spark, Kafka, Storm, etcKnowledgeable with Data Science tools and frameworks. Collaborate with cross-functional teams to understand data needs and deliver solutionsStay updated with the latest industry trends and advancements in big data technologies, particularly in healthcare applications, and proactively suggest improvements to enhance data processing processes and tools.
$140,000 - $200,000 a yearFull-timeExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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Must have: Oracle PL/SQL development, SQL Server, UNIX Shell Scripting and JavaScript Good to have: Informatica, Kafka and Big data integration with Hadoop." Must have: Oracle PL/SQL development, SQL Server, UNIX Shell Scripting and JavaScript Good to have: Informatica, Kafka and Big data integration with Hadoop.
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10+ years of experience including 3+ experience with big data systems, analytics, containerized microservices, serverless functions, and event-driven architecture. Thorough understanding/working knowledge of CI/CD systems using Jenkins and integration with source control systems like GitHub/GitLabExperience using industry-standard messaging systems like Kafka/RabbitMQStrong experience using NoSQL databases like MongoDB, CassandraExperience using spark and spark SQL.2+ years working directly with end customers to assess needs, identify solutions, and constructively resolve disagreements.
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Advance experience with developing Data Pipeline, ETL/ELT, utilizing tooling of Big Data Platform, Datalake, Synapse, Airflow, AirByte, Snowflake. Experience with Data Ingestion/ streaming tooling such as ADF (Azure Data Factory), Kafka, Five Tran, Spark, or similar technologies.
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3+ years of experience in open source frameworks (Kafka) The team will be pivoting towards creating real-time, personalized collections experiences using open sourced, cloud-based, and API/data streaming technology.
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You also have:Hands-on experience in testing and validating ETL pipelines and knowledge of big data frameworks and architectures, including Spark, Hadoop/MapReduce, Airflow, and Streaming (Kafka or similar message bus.
Full-timeExpandApply NowActive JobUpdated 9 days ago - UpvoteDownvoteShare Job
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Experience with Big Data Technologies ( i.e., Hadoop, HDFS , MapReduce, Hive, Pig, Spark, etc. Experience using modern technology ( e.g., Java, Cassandra, Kafka) and design patterns (microservices, APIs , streaming.
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Experience with big data tools and platforms, such as Hadoop, Spark, or Kafka. Our client is adding a Data Science Software Engineer to a small team of top performers focused on developing complex, AI-based algorithms and forecasting applications in the financial industry.
ExpandApply NowActive JobUpdated 10 days ago - UpvoteDownvoteShare Job
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Big data systems (Cassandra, Neo4j, Spark, HBase) - Messaging queues (e.g. Kafka, MQ, RabbitMQ) Container technologies (Docker, Kubernetes, DCOS, Rocket, Mesos) - Must. Messaging queues (e.g. Kafka, MQ, RabbitMQ.
ExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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Experiences working on Big Data tech stack e.g., Hive, Spark, Kafka, Flink etc. We integrate our functionalities deeply into Apache's big data ecosystem (Spark, Hive Presto), and build world-class data security & privacy framework to support high efficient and seamless data life cycle management.
$224,000 - $410,000 a yearFull-timeExpandApply NowActive JobUpdated 10 days ago - UpvoteDownvoteShare Job
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Key Required Skills: Extensive experience in Design, implementation; support data ingestion, and consumption pipelines for enterprise-scale datasets using Big Data tools, such as Kafka, Spark, Oozie, Hive, MapReduce, Flume, Pig, Scala, Python, and Java Requirements Basic Qualifications: Bachelors Degree in Computer Science, Mathematics, Engineering or a related field with 7+ years of experience.
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Data Engineering & Backend Proficiency: 7+ years of experience as a Big Data Engineer or Backend Engineer, demonstrating a strong understanding of data systems design and development.
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