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Demonstrated commercial experience in data modeling, design, and development for relational databases with complex SQL (Snowflake, BigQuery, Redshift. Demonstrated experience in cloud engineering, including serverless architecture, and/or data streaming services (AWS Lambda, Kafka, etc.
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Extensive hands-on experience implementing data migration and data processing using AWS services: VPC/SG, EC2, S3, AutoScaling, CloudFormation, LakeFormation, DMS, Kinesis, Kafka, Nifi, CDC processing Redshift, Snowflake, RDS, Aurora, Neptune, DynamoDB, Cloudtrail, CloudWatch, Docker, Lambda, Spark, Glue, Sage Maker, AI/Client, API GW, etc.
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Familiarity with the Technology stack available in the industry for data management, data ingestion, capture, processing and curation: Kafka, StreamSets, Attunity, GoldenGate, Map Reduce, Hadoop, Hive, Hbase, Cassandra, Spark, Flume, Hive, Impala, etc.
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Data platform: Hadoop, Hbase, OpenSearch, Kafka, Spark, Flink, Go, Java, SQL, Databricks, Snowflake, BigQuery. Experience with big data and workflow management technologies like Hadoop, Spark, Redshift, Athena, Airflow, etc.
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Experience with distributed data and computing tools, including Spark, Databricks, Hadoop, Hive, AWS EMR, or Kafka. Experience with data warehousing using AWS Redshift, MySQL, or Snowflake.
$93,300 - $212,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Development languages/frameworks : Java/Scala, Apache Spark, Kafka, Vertica, JavaScript (React / Redux), MicroStrategy. Design, develop, and maintain high volume Java and Scala based data processing jobs using industry standard tools and frameworks in the Hadoop ecosystem, such as Spark, Kafka, Hive, Impala, Avro, Flume, Oozie, and Sqoop.
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We are seeking a skilled Software Engineer with experience in design and development of infrastructure using Java, Spring Framework modules, Spring boot, Micro Services, AWS, Kafka, Docker, cloud-based java applications, JSP, Hibernate, Web services (soap and Rest), Maven, Unit Testing (JUnit), MySQL, Oracle, Jenkins, code quality tool Sonar.
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4+ years experience with Distributed data/computing tools (Glue, Airflow, EMR, ECS Fargate, Kafka, Spark, Aurora, or MySQL) Utilize programming languages like Scala, Python and Open Source RDBMS and NoSQL databases and Cloud based data warehousing services such as Redshift and Snowflake.
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3+ years of hands-on experience in AWS and Big Data technologies such as S3, Lambda, LakeFormation, DMS, Kinesis, Kafka, Redshift, RDS, Aurora, Neptune, DynamoDB, ECS, Glue, DataBrew, Python, R-Studio, SageMaker, Spark/SparkSQL, Eventbridge, as well as programming in Python, Java, Spark, SQL, Unix shell/Perl scripting, etc.
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Blob storage, Redshift, Kafka, Hadoop, Spark, Hive etc. Experience with cloud-based data platforms (e.g., AWS, Azure, GCP) and associated services (e.g., S3, Redshift, BigQuery). Experience with data streaming and real-time data processing frameworks (e.g., Kafka, Apache Flink, AWS Kinesis, etc.
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Develop, deploy and maintain data processing pipelines using cloud technology such as AWS, Kubernetes, Lambda, Kafka, Airflow, Redshift, S3, Glue, and EMR. 8+ years experience in engineering data pipelines using data technologies (Python, Databricks, pySpark, Kafka) on large scale data sets.
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Designs, modifies, develops, and implements solutions for ingesting, provisioning and securing data in the Lake (S3), Warehouse (Redshift) and Marts (Redshift and MySQL) using Scala, Apache Spark, Hive, Apache Pig, MapReduce, AWS Data Pipeline, AWS Glue, AWS EMR and Apache Kafka.
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Data: Good understanding of data & data processing tools (e.g. Spark, Kafka, SQL), of relational database technologies and of analytics databases (e.g. Redshift, Vertica, Snowflake) Spark, Kafka, SQL), of relational database technologies and of analytics databases (e.g. Redshift, Vertica, Snowflake.
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Familiarity with data integration techniques, ETL frameworks (e.g., Apache Spark), and workflow management tools (e.g., Airflow). Experience with data engineering tools and frameworks such as Apache Airflow, Apache NiFi, Talend, etc.
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Familiarity with Hadoop, Spark, and Cloud databases (Snowflake, BigQuery, Redshift, Databricks) and stream processing frameworks (Kafka, Kinesis). Familiarity with Hadoop, Spark, and Cloud databases (Snowflake, BigQuery, Redshift, Databricks) and stream processing frameworks (Kafka, Kinesis.
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