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Solid understanding of various Data Management and Data Pipeline tools available in AWS. Working knowledge with primary AWS Services like S3, Lambda, Batch, Glue, Athena, EC2, EBS, CloudWatch, CloudTrail, ECS, ECR, EMR, IAM, SNS etc.
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Familiarity with the following technologies: Hadoop, Kafka, Airflow, Hive, Presto, Athena, S3, Aurora, EMR, Spark. Experience utilizing or leading implementations leveraging ETL tools (Informatica / Talend), BI Reporting tools such as MicroStrategy, Microsoft Power BI, data modeling tools such as Erwin, Oracle, SQL server, NoSQL, JDBC, UNIX shell scripting, PERL and JAVA, XML/JSON files, SAS , Python, AWS cloud-native technologies, S3, Athena, Redshift.
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Expert in Spark, Parquet, steaming, events, Kafka, telemetry, MapReduce, Hadoop, Hive, Presto, Spark, data query approaches, and dashboarding. Knowledge of Cloud solutions like Kendra, SageMaker, Auto-ML, Big Query, RedShift, Glue, Athena.
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Experience working in AWS environment primarily EMR, S3, Redshift, Athena, etc. Good understanding of Hadoop and Big Data processing frameworks. Experience working in AWS environment primarily EMR, S3, Redshift, Athena, etc.
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Experience with AWS services such as Athena, Glue, Lambda, S3, DynamoDB, NoSQL, Relational Database Service (RDS), Amazon EMR and Amazon Redshift. Extensive experience working with RDBMS, Spark, Hadoop, Kafka.
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Experience in technologies such as Hadoop, Spark, Kafka, Redis, Cassandra, Pandas, Dask, Airflow, Apache Beam, MongoDb, Hive, Impala, Hazelcast, Athena, Presto. Experience in technologies such as Hadoop, Spark, Kafka, Redis, Cassandra, Pandas, Dask, Airflow, Apache Beam, MongoDb, Hive, Impala, Hazelcast, Athena, Presto.
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Familiarity with AWS and cloud native data processing tools like Redshift, Presto, EMR, Glue, Athena, SageMaker. 5+ years of hands-on experience in architecting Big Data applications using the Hadoop ecosystem, such as Hadoop (HDFS, YARN, MapReduce), Spark (Spark SQL Spark Streaming, MLLib), Pig, Hive, HBase, Sqoop, Oozie.
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6+ years’ experience working within the AWS Big Data/Hadoop Ecosystem (EMR, Glue and Athena) Experience in Hadoop, HDFS, Hive, Presto, REST/SOAP API, Spark2, Airflow is a plus. Work with AWS big data technologies including EMR, Glue, S3, EKS, Lambda, Athena, RDS.
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Our client, a leader in global market access, is looking for a Sr. Data Architect. Knowledge and understanding of CI/CD pipelines and infrastructure as code (IaC) Team Lead. Their ideal candidate will work with their enterprise architect to develop a program, run as process owner, and build/configure acquire tooling to support the program.
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AWS Athena, Apache Spark, Hadoop, Hive. AWS Athena, Apache Spark, Hadoop, Hive. Tableau, PowerBI, Qlik. Advance Analytics: Python, R Studio, AWS, Azure, Google Cloud. AWS Sagemaker, Azure Machine Learning Studio.
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And experience with large-scale, big data methods, such as MapReduce, Hadoop, Spark, Hive and SAAS model platforms like Databricks, Cloudera, etc. Understanding of Amazon Web Services native tools like S3, Kinesis, Redshift, EMR, Athena, Lambda, Quick sight, and others.
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5+ years experience with big data and data warehousing technologies such as Snowflake, Redshift, Databricks, cloud Data Lakes, Spark, Hadoop, Parquet, etc. 5+ years experience operating and deploying solutions using AWS Services including S3, EMR, SQS, SNS, Lambdas, Athena, Glue and streaming services including Kinesis and Kafka.
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Experience with big-data technologies such as Hive, Hadoop, Presto/Trino, Spark, Iceberg and Avro. Advanced understanding of cloud native services, including AWS managed offerings such as Glue, Athena, EMR.
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Experience with big data and workflow management technologies like Hadoop, Spark, Redshift, Athena, Airflow, etc. Data platform: Hadoop, Hbase, OpenSearch, Kafka, Spark, Flink, Go, Java, SQL, Databricks, Snowflake, BigQuery.
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EMR, Glue, Athena, and Redshift. Experience with Hadoop, Hive, Spark, or other data processing tools. 4+ years using Spark and other Hadoop ecosystem software. EMR, Glue, Athena, and Redshift.
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