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Experience with cloud computing platforms (, AWS, Azure, GCP) and cloud native computingProficiency in programming languages like Python, Java, Scala, C#, SQLExpertise in big data technologies such as Hadoop, Spark, Kafka, and NoSQL databasesKnowledge of data modeling, ETL processes, and data warehousing conceptsExceptional problem-solving abilities and teamwork skills.
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Implement data processing and transformation workflows using Databricks, Apache Spark, and SQL to support analytics and reporting requirements. Strong experience with Databricks and Apache Spark for data processing and analytics.
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Track record of thought leadership and innovation around Big Data. Solid understanding of Cloud Computing Technologies and related emerging technology (e.g. Amazon Web Services EC2, Elastic MapReduce, Azure, GCP) and considerations for scalable, distributed systems Knowledge of NoSQL platforms (e.g. key-value stores, graph databases, RDF triple stores.
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Experience with at least one major Massively Parallel Processing (MPP) or cloud database technology (Snowflake, Redshift, Big Query) The Data Capture team for the Data organization within the DE&ET organization is in search of a Lead Software Engineer.
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Develop Scalable Solutions: Architect and deploy robust, efficient, and scalable data pipelines and modeling solutions using cloud-based technologies (e.g., OpenShift, Docker, GCP) and programming languages like Python, BigQuery, Spark, etc.
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Experience with SQL, data visualization tools, and cloud-based analytics platforms highly preferred (Snowflake, Databricks, Redshift, BigQuery) The award-winning software was built to capitalize on the performance power of cloud data warehouses to combine data sources and analyze billions of rows of data instantly via an intuitive, spreadsheet-like interface – no coding required.
$135,000 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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Utilizing knowledge of modern big data approaches preferred: e.g. PySpark, Apache Spark, Azure Databricks, Azure SQL, Azure ML, R, Python, Java, etc. Leveraging knowledge of performing data ETL (Extract, Transform and Load), and utilizing experience with SQL, Alteryx, Power Query and other agile technologies.
$202,000 a yearFull-timeExpandApply NowActive JobUpdated 2 days ago - UpvoteDownvoteShare Job
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4+ Experience with technologies Apache Mesos, Marathon, or Apache Spark. At least 3 years of experience in Cloud Native technologies (Amazon Web Services, Microsoft Azure, Google Cloud Platform.
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Daily Tasks: Skills in nutshellDrupal, PHP, Angular, Express with Angular Universal, NodeJS Monitoring (PM2), SOLR, Java, AWS Cloud Engineering, AWS Cloud Services, Route 53, Load Balancers, EC2, Acquia CloudAutoscaling groups, Mem Cache, Secrets Manager, CloudFront, Code Deploy, Code Pipeline, VPC, CloudFormation, IAM,Secuirty Groups, S3, CloudWatch, EFS, WebSphere Portal,Ansible, Apache, Ngnix, NodeJS, Varnish, Jenkins, Terraform, LSyncD, Bash Scripting, Splunk.
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Knowledge of public clouds (AWS, Azure, GCP) with familiarity in data warehousing solutions like Snowflake and Databricks. Proficiency in SQL, Python, R, Apache Spark or similar product or language is a plus.
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2+ years of cloud computing engineering experience in one or a combination of the following: Amazon Web Services (AWS), Google Cloud Compute (GCC), Azure Cloud Security or Pivotal Cloud Foundry (PCF.
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As a team, we have expertise in cloud platforms, data engineering, data analytics, and data science, machine learning, and generative AI. As a member of our team, you will exercise and grow your expertise in those areas, using open-source projects such as Apache Spark™, Delta Lake and MLflow.
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Previous experience as a DevOps/DevSecOps Engineer supporting applications and platforms running in private or public cloud (such as Rancher, Anthos, AWS, GCP, VMWare). You will also be responsible for driving for secure code design and integration of our software stack to keep our customers’ data safe while focusing on mitigating attack risks, securing cloud transformation, and fostering a culture of security and reliability within the company.
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Data Conversion and Integration Experience: Demonstrated experience with Oracle HCM Cloud data conversions and integration tools, including Oracle Integration Cloud (OIC), BI Publisher, HCM Extracts, HDL (HCM Data Loader), UCM, and managed file transfer (MFT) tools.
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TRKKN is a full service provider for the Google Marketing Platform and Google Cloud with an interdisciplinary team of experts from the fields of Digital Analytics, Conversion Optimization, Ad Tech, Advanced Analytics & AI, Cloud Engineering and Tech & Data Strategy.
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cloud engineer gcp big data apache spark jobs Title: engineer Company: Cobank in Newark, NJ
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