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O Programming Language: Python, R, SQL, Java, Scala, Pyspark/Apache Spark, Shell scripting. Use programming languages including but not limited to Python, R, SQL, Java, Scala, Pyspark/Apache Spark, Shell scripting.
ExpandApply NowActive JobUpdated 4 days ago - UpvoteDownvoteShare Job
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Desired experience in: Looker / Google Data Studio, BigQuery, Apache Airflow / Google Cloud Composer. Experienced with Google Cloud Composer / Apache Airflow or similar data orchestration services.
RemoteExpandApply NowActive JobUpdated 4 days ago - UpvoteDownvoteShare Job
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This architecture includes an Databricks, Microsoft Azure platform tools (including Data Lake, Synapse), Apache platform tools (including Hadoop, Hive, Impala, Spark, Sedona, Airflow) and data pipeline/ETL development tools (including Streamsets, Apache NiFi, Azure Data Factory.
ExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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Strong proficiency in Java Stack programming with expertise in the Spring Boot framework, Apache / Tomcat, Apache Maven, Apache Spark, API Concepts and Methodologies, API Security, Camunda, Cloud Automation, Cloud Computing, Cybersecurity, Data Engineering, Database Design (Physical), DevOps, Java and Related Technology, JavaScript, Linux.
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Mandatory Certificate : Databricks Certified Associate Developer for Apache Spark. Hands-on experience on Apache Hadoop ecosystem components like MapReduce, Sqoop, Pig, Hive, HBase, Spark, Kafka, Oozie, Flume, Zookeeper.
ExpandApply NowActive JobUpdated 8 days ago - UpvoteDownvoteShare Job
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This role will provide expertise to support the development of a Big Data / Data Lake system architecture that supports enterprise data operations for the District of Columbia government, including the Internet of Things (IoT) / Smart City projects, enterprise data warehouse, the open data portal, and data science applications.
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Experience with cloud data processing and analytics services such as AWS Glue, Google Dataflow, Apache Spark on cloud platforms, or Azure Data Lake Analytics. Familiarity with cloud data storage solutions such as AWS S3, Google Cloud Storage, Azure Blob Storage, AWS Redshift, Google BigQuery, Azure SQL Data Warehouse, or others.
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The Data Solution Architect must have familiarity with traditional data technologies (Data Warehouse, Data Lake) as well as transformative capabilities such as Data Lakehouse, Data Fabric, and Data Mesh in order to define go-forward strategies which are compliant for US Govt clients – including addressing Federal Cloud security requirements, data privacy, data security, and data integration approaches which are approved for US Govt use.
$123,000 - $231,000 a yearFull-timeExpandApply NowActive JobUpdated 4 days ago - UpvoteDownvoteShare Job
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Experience with relational databases and building modern data pipelines Hands-on experience working with cloud technologies (OCI, AWS, Azure, GCP) Familiarity with Big Data components like Apache Spark, Apache Hudi, etc.
$96,800 - $251,600ExpandApply NowActive JobUpdated 4 days ago - UpvoteDownvoteShare Job
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Extensive hands-on experience with Apache Spark, Kafka streaming for large-scale data processing and analytics. Good experience and understanding of operationalization of large scale data and analytics solutions on Snowflake Cloud Data Warehouse.
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Experience with distributed or parallel programming frameworks, including Apache Spark or NVIDIA CUDA, and infrastructure as code (IaC) frameworks and services, including Terraform or CloudFormation.
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Looking for a Data Engineer who possesses the following skills: data warehouse design and development, Spark ETL/ELT development, Airflow DAG development, and data mapping and analytics.
ExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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Develop Data Pipelines using Scala and Spark EMR to move data into our consolidated data lake or data warehouse (Snowflake) Expert and Hands-On development in distributed computing environment using Hadoop, Scala, Spark and Apache Airflow.
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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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Utilizing technologies such as Scala, Apache Spark, Hive, Apache Pig, MapReduce, AWS Data Pipeline, AWS Glue, AWS EMR, Apache Kafka, and hands-on experience with Talend, the engineer contributes to the entire data processing lifecycle.
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