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The Lead Data Engineer is responsible for orchestrating, deploying, maintaining and scaling cloud infrastructure targeting big data and platform data management (e.g., data warehouses, data lakes) including data access APIs. Prepares and manipulates data using Hadoop or equivalent.
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Job Title: Data Engineer/ Data ArchitectLocation: Corvallis, OR – 5 Days Onsite Role Job Description: At least 8 to 10+ years’ experience in data engineering , AI and ML and Aws/Azure Architect, Design and implement distributed data processing pipelines using Spark, Python, SQL and other tools and languages prevalent in the Big Data/Lakehouse ecosystem.
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Big Data Technologies: Proficient with big data technologies such as Databricks, Hadoop, Spark, and Kafka. Leverage big data technologies to efficiently process and analyze large datasets, particularly those encountered in a federal agency.
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The big data architect will support the development of autonomous driving software solutions by playing the role of subject matter expert for the big data systems, underlying data and data products.
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Experience with big data technologies Hadoop, Spark) and cloud platforms AWS, Azure). We are seeking a talented and experienced Data Scientist to join our team onsite at Warner Robins Air Force Base (AFB), GA. This role is integral to harnessing data to support mission-critical decisions in a secure defense environment.
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Empresa global de capital privado especializada en outsourcing de innovación, dedicada a la prestación de servicios de desarrollo y diseño de software, modernización de aplicaciones, RPA, machine learning y Big Data, entre otros.
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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.
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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.
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Technical Proficiency: Expertise in SQL and programming languages such as Python; familiarity with big data technologies like Apache Hadoop, Spark, and Kafka. Professional Experience: At least 5 years of experience in data engineering, with a strong focus on data integration and pipeline construction in cloud environments and enterprise data warehouses like Snowflake.
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Plant monitoring and care during vegetative and flowering phase: trimming and staking; big leafing and pruning; plant care, watering and feeding; plant monitoring and climate control; pest and disease control; inventory data input.
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Advanced experience in SQL in big data warehouse systems such as Snowflake, BigQuery, Databricks, etc. Internal knowledge of open source or related big data technologies. As a member of the Data Engineering Web3 team, you own the ETL/ELT pipelines and data warehouse that are used to analyze trends and activity in our Web3 product offerings.
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The courses may include Foundations of Data Analytics and Programming, Advanced Excel for Data Analytics, Data Governance, Management and Quality, Data Visualization-Power BI, Data Visualization-Tableau, Data Privacy and Integrity, Data Protection, Descriptive Analytics, Predictive Analytics, Data Complexity, Cloud Analytics, Big Data, various programming courses and concepts involving python, r and ML, and database courses (including MySQL, Microsoft SQL Server and NoSQL alternatives.
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Develop and optimize Databricks notebooks for big data processing and analytics in Azure Databricks environments. Expertise in SQL Server Management, Azure Data Factory Development, Databricks Engineering, Delta Parquet File Management, and SQL Server Integration Services.
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Expertise in Cloudera Big Data Technologies, including Cloudera Distribution of Hadoop (CDP), Apache Hadoop, Apache Spark, Apache Hive, Apache Impala, and Apache HBase, with hands-on experience in deploying, configuring, and optimizing these technologies for large-scale data processing and analytics.
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A master’s degree in computer science, Data Science, Big Data, Applied Statistics, Bioinformatics, or a closely related computational field. Hands on experience with cloud services for data storage and processing, including but not limited to Databricks, Azure SQL Database, Google Cloud Spanner and BigQuery.
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big data jobs Title: data Company: Remoteworker Us in ME, Wyoming
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