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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. Data Processing and Transformation: Implement data processing and transformation workflows using cloud-native services such as AWS Glue, Google Dataflow, or Azure Data Factory.
$210,000 a yearFull-timeExpandApply NowActive JobUpdated 2 months ago - UpvoteDownvoteShare Job
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Certification in cloud platforms (e.g., AWS Certified Solutions Architect, Google Professional Data Engineer). - Familiarity with additional data processing frameworks/tools like Apache Spark, dbt, or Kafka.
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Leverage cloud platforms (e.g., AWS, Azure, Google Cloud/BQ, Databricks) for scalable and efficient data processing and storage. The candidate should have expertise in data modeling, SQL, Python, R, data warehousing, big data technologies, data pipeline construction, data quality, cleansing, version control, cloud services, machine learning, feature engineering, deep learning, and natural language processing.
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Design, develop, monitor, and maintain data pipelines in an AWS Gov Cloud ecosystem with AWS, Databricks, Delta Lake and Trino as the underlying platforms. Optimize data processing and query performance for large-scale datasets within AWS and Databricks environments.
$200,400 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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Three years of development experience with cloud services ( AWS,GCP,AZURE) utilizing various support tools (e.g. GCS, Dataproc, Cloud Data flow, Airflow(Composer), Kafka , Cloud Pub/Sub.
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4+ years of experience in building data lake, cloud data platform leveraging cloud (GCP/AWS) cloud native architecture, ETL/ELT, and data integration; Expertise in developing distributed data processing and Streaming frameworks and architectures (Apache Spark, Apache Beam, Apache Flink.
Full-timeExpandApply NowActive JobUpdated 14 days ago - UpvoteDownvoteShare Job
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Experience with AWS cloud services : EC2 , EMR, RDS, Redshift , Modern data platforms, Snowflake , dbt , Fivetran and Airflow. Lead Data Engineer is responsible for managing and organizing enterprise data and overseeing the technical output of a team of data engineers.
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Priority needs are cloud formation and event-based data processing utilizing SQS to support ingestion and movement of data from Workday to AWS Redshift for consumer and analytic use.
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As an AWS Data Engineer, you will be responsible for designing, building, and maintaining scalable data pipelines on AWS cloud infrastructure. Design, develop, and deploy end-to-end data pipelines on AWS cloud infrastructure using services such as Amazon S3, AWS Glue, AWS Lambda, Amazon Redshift, etc.
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Build large-scale batch and real-time data pipelines with data processing frameworks in AWS, Azure or GCP cloud platform. As a Sr. Data Engineer, you will be part of a talented team of engineers responsible for the deployment and configuration of cloud resources to meet individual client business needs in AWS. Client engagements cover a wide variety of business requirements and require our engineers to adapt quickly and stay on top of recent cloud technology trends.
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Professional certifications in cloud computing (e.g., AWS Certified Solutions Architect, Microsoft Certified Azure Solutions Architect, Azure Data Engineer, SnowPro Core) and/or big data technologies.
Full-timeExpandApply NowActive JobUpdated 30 days ago - UpvoteDownvoteShare Job
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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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Design, implement, and maintain complex ETL pipelines using tools such as Apache Spark, Apache Airflow, and AWS Glue for both batch and near real-time data processing. Proficiency in SQL, Python, and familiarity with cloud-native services on AWS, GCP, or Azure, including Redshift, BigQuery, or Synapse Analytics.
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In-depth knowledge of big data technologies such as Hadoop, Spark, Kafka, and cloud platforms such as AWS, Azure, GCP, Snowflake, Databricks, etc. Provide technical expertise and guidance on the selection, and hands-on implementation, and optimization of big data platforms, tools, and technologies across multiple cloud environments (e.g., AWS, Azure, GCP, Snowflake, etc.
$276,100 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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Hands-on experience extracting (ETL using CDC, Transaction Logs, Incremental) and processing large data sets for Streaming and Batch data loads. RSM is looking for an experienced Hands-On Technical Sales Director with expertise in big data technologies and multi-cloud platforms to lead our technical team for the financial services industry.
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data processing aws cloud jobs Title: data engineer sr Company: Keylent Inc in Pelham, New Hampshire
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