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We are hiring a talented Senior Big Data Engineer to build cloud-based data pipelines for machine learning, data processing with Apache Spark, and database development. Bachelors Degree required from an accredited, not for profit university or college, with degree preferably in Computer Science, Data Science, or related field.
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This role requires a deep understanding of big data technologies, particularly Apache Spark, as well as expertise in data engineering and analytics. Proven experience as a Technical Lead with a focus on Databricks and big data technologies.
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Apply your skills with Databricks, using Python, and big data streaming to pioneer client technologies and data. Experience with large-scale distributed computing and big data technologies (databricks etc.
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Training & Certifications: Splunk , AWS, Big Data/Cloudera, VMWare, Scrum Master. The Sponsor seeks assistance with performing technical project management that spans technical data analysis, information technology security research, data integration, software evaluation, and graphical visualization disciplines for multiple projects using the Sponsor’s enterprise IT systems.
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As a big data engineer at Booz Allen, you’ll implement data engineering activities on some of the most mission-driven projects in the industry. We need an experienced data engineer like you to help our clients find answers in their big data to impact important missions—from fraud detection to cancer research to national intelligence.
$75,600 - $172,000 a yearExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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As a data engineer, you know that organizing big data can yield pivotal insights when it’s gathered from disparate sources. Work with us to use big data for good. Experience with distributed data and computing tools, including Spark, Databricks, Hadoop, Hive, AWS EMR, or Kafka.
$58,400 - $133,000 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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Experience with data warehousing, including AWS Redshift, MySQL, or Snowflake. Ever-expanding technology like IoT, machine learning, and artificial intelligence means that there’s more structured and unstructured data available today than ever before.
$73,100 - $166,000 a yearFull-timeExpandApply NowActive JobUpdated 11 days ago - UpvoteDownvoteShare Job
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Experience solving Big Data batch and real-time data processing problems, with large-scale analytics and data processing engines such as Apache Spark and Databricks. Knowledge of Python data science tools, such as SciKit, Numpy, TensorFlow, Jupyter.
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Implement data processing pipelines using Azure Data Factory, Databricks, Azure Machine Learning, Azure Logic Apps, Azure Function Apps, Azure Kubernetes container and other big data services.
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Delivery experience in Data Engineering with Google Cloud Platform including Big Query, Dataflow, Cloud Data Fusion, Cloud Composer, Dataproc, Cloud Pubsub, Cloud Function etc. + Propose, own initiatives and demonstrate though leadership that improve the efficiency and productivity of the data science Center of Excellence.
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Applies a solid understanding in one or more of these areas (IT General Controls, Cybersecurity, Cloud operations, Data governance, Data privacy compliance, or Big Data) to execute technical audits or other risk and compliance-related initiatives in order to identify, assess, and explain risks, report findings, and develop and communicate recommendations.
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GAI's team members work side by side with government IT executives and OEM partners to solve complex business problems such as AI/ML, RPA, Cyber Security, Big Data, Data Center & Cloud.
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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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Data science techniques such as predictive analytics, machine learning, natural language processing and business intelligence, including use of big and non-tabular data. Advanced skills in statistical analysis using Stata, SPSS, R, SAS, or SQL for the purpose of Advanced skills in using data visualization platforms such as advanced Excel visualizations, Tableau, PowerBI, Metabase, Google Data Studio, etc.
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Experience with data engineering and big data technologies such as Apache Airflow, Trino, and AWS EMR. Experience using Infrastructure as Code (IaC) best practices for provisioning and configuring cloud services including experience tools such as Terraform or AWS CDK.
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big data jobs Company: Jobot in Arlington, VA
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