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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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Experience in developing partner led sales in collaboration with data platform and tool vendorsIn-depth knowledge of big data technologies such as Hadoop, Spark, Kafka, and cloud platforms such as AWS, Azure, GCP, Snowflake, Databricks, etc.
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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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YOUR SKILLS AND EXPERTISEBachelor’s degree in computer science, data science or a related field with five (5) or more years of working as a data engineer, ETL developer and/or data warehouse DBA.STANDOUT QUALIFICATIONS:Experience with Cloud-based data services and solutions (Azure Synapse / Data Lake, AWS RedShift, Snowflake, GCP Big Query)Experience partnering with Analytics and Data Science teams in building out production grade GenAI/ML solutions.
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Experience with big data tools and architectures, such as Cloudera Hadoop, HDFS, Hive, and Spark. THE ROLE:As a key member in the Advanced Data Analytics team, the Data Analyst will work with this and a cross-functional team to develop and execute the data analytics strategy and apply to Oshkosh Corporation products.
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YOUR IMPACT:Design and develop scalable Change Data Capture (CDC) and ETL solutions to deliver data from source systems to analytics platforms (structured and unstructured; batch and streaming.
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Familiarity with Change Data Capture solutions (Qlik Replicate, Striim, Debeezium, etc. Advanced Data Analytics wok encompasses the acquisition, processing and machine learning of engineering or service data and application to preventive maintenance and intelligent control of on or off-road vehicles.
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Assist in ensuring proper data governance (quality security, etc. within the data lake and enterprise data warehouse systems across all business segments. Assist in education others on best practices surrounding data work (i.e. data modeling, database design, ETL design, job scheduling and monitoring, etc.
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Big Data Platforms : Experience with Databricks for big data processing and analytics. Certifications : AWS Certified Solutions Architect or AWS Certified Big Data – Specialty.
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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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Specific experience in writing Big Data engineering for large-scale data integration in AWS; prior experience in writing Machine Learning data pipelines using Spark programming language is an added advantage.
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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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Experience of implementing Amazon EMR or Big Data technologies like Hadoop, Spark, Presto, Hive will be a plus. Implementation experience of Big Data technologies like Hadoop, Spark, Presto, Hive, and Hue will be a major advantage.
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At least 4 years of experience in data engineering working with Big Data Technologies: Apache Spark, Pyspark, Hadoop, and DataBricks with delta lake. Requires a minimum of a bachelor's or foreign equivalent degree in Management Information Systems, Computer Science and Engineering, or a related field plus 4 years of experience as a software developer, data engineer, or related occupation.
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In HADOOP , you'll be given an introduction to BIG DATA, APACHE HADOOP, HADOOP ECOSYSTEM, CLOUDERA QUICKSTART VM along with core concepts of the Hadoop framework including MapReduce, HIVE, PIG, SQOOP, FLUME, HBASE, OOZIE.
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big data jobs Company: Raising Cane's in ND, Connecticut
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