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Integrate Python, AWS services (such as S3 and EMR), Redshift, Snowflake, Hadoop, Hive, Spring, Hibernate, Cassandra, Kafka, and ETL processes into Spark applications. Advanced - Python, AWS, Redshift, Snowflake,Hadoop, Hive, Spring, Hibernate, Cassandra, Kafka, ETL.
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Advanced Scala, Python, AWS, Redshift, Snowflake,Hadoop, Hive, Spring, Hibernate, Cassandra, Kafka, ETL, Advanced Scala, Python, AWS, Redshift, Snowflake,Hadoop, Hive, Spring, Hibernate, Cassandra, Kafka, ETL.
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Expertise in Java/Scala/Python, SQL, Scripting, Teradata, MicroStrategy, Oracle, MySql, SQL Server, Hadoop (Sqoop, Hive, Pig, Map Reduce), Spark (Spark Streaming, MLib), Kafka or equivalent Cloud Bigdata components (specific to the Platform Engineering role.
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Tech stack: Google cloud, HDFS, SPARK, Scala, Python (optional), Automic/Airflow, BigQuery, Kafka, API, Druid. Expertise in big data technologies like Hadoop, Apache Spark (Scala preferred), Apache Hive, or similar frameworks on the cloud (Google Cloud Platform preferred, AWS, Azure etc.
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Data Science, Big Data, AI, Artificial Intelligence, ML, Machine Learning, AdTech, Advertising Technology, Demand-Side Platform (DSP), Programmatic Advertising, Python, AWS, Hadoop, Spark, Kafka, Data Warehousing.
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6+ years of experience in administration and support of NextGen Platforms built with Cloudera (CDH and CDP) and Big Data Technologies such as Hadoop, Flume, Solr, NiFi, HBase, Hue, Impala, Kafka, Kudu, Oozie, Spark, YARN, ZooKeeper, etc.
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Blob storage, Redshift, Kafka, Hadoop, Spark, Hive etc. Experience with data streaming and real-time data processing frameworks (e.g., Kafka, Apache Flink, AWS Kinesis, etc). Familiarity with data integration techniques, ETL frameworks (e.g., Apache Spark), and workflow management tools (e.g., Airflow.
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Scale and operationalize privacy and security systems in a big data environment leveraging technologies like Spark, Kafka, Presto, Flink, Hadoop in both on-premise and AWS environment through automation and infrastructure-as-code.
ExpandApply NowActive JobUpdated 44 days ago - UpvoteDownvoteShare Job
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Streaming systems (e.g., Apache Flink, Apache Kafka), resource management systems (e.g., Apache Mesos, Kubernetes), or Identity and Access Management (e.g. Apache Ranger, Sentry, OPA) 3+ years of experience scaling and operating distributed systems like big data processing engines (e.g., Apache Hadoop, Apache Spark), distributed file systems (e.g. HDFS, CEPH, S3, etc.
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Skills: Databricks, Azure, AWS, PaaS (platform as a service), apache kafka/kafka, terraform, Hortonworks, hadoop, Unity Catalog, administration, 2+ years of Apache Kafka streaming platform administration.
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Data Infrastructure, Spark, Kafka, Presto, Flink, Hadoop, AWS, EC2, S3, RDS, IAM, Kubernetes, Python, Java, Cassandra. Scale and operationalize big data technologies like Spark, Kafka, Presto, Flink, and Hadoop in both on-premise and AWS environments.
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Tech Skills - Scala, Spark, GCP, Dataproc, Hadoop, Airflow, SBT, Maven, Docker, Kubernetes, pyspark, Jenkins, Bigquery. Knowledge and experience in Kafka, Storm, Druid and Presto. Experience running spark/Hadoop workloads using Dataproc, Dataflow, Cloud composer, EMR, HD Insights or similar.
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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 83 days ago - UpvoteDownvoteShare Job
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Data Technologies: Kafka, Spark, Hadoop, Presto, Alloy – a data management and data governance platform. Kafka, Spark, Hadoop, MongoDB, ElasticSearch, MemSQL, Sybase IQ / ASE.
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3+ years of experience with Big Data tools/technologies like Hadoop, Spark, Spark SQL, Kafka,Sqoop, Hive, S3, HDFS, or. Strong knowledge of Messaging Platforms like Kafka, Amazon MSK & TIBCO EMS or IBM MQ Series.
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