Data Engineer

⭐ - Featured Role | Apply direct with Data Freelance Hub
🌎 - Country
United States
πŸ’± - Currency
$ USD
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πŸ’° - Day rate
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πŸ—“οΈ - Date discovered
September 9, 2025
πŸ•’ - Project duration
Unknown
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🏝️ - Location type
Unknown
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πŸ“„ - Contract type
Unknown
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πŸ”’ - Security clearance
Unknown
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πŸ“ - Location detailed
Auburn Hills, MI
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🧠 - Skills detailed
#SQL (Structured Query Language) #Business Objects #Unix #Data Architecture #Computer Science #Data Modeling #QlikView #Hadoop #BO (Business Objects) #"ETL (Extract #Transform #Load)" #Sqoop (Apache Sqoop) #Data Mining #Data Engineering #NLP (Natural Language Processing) #Linux #ML (Machine Learning) #DataStage
Role description
Job Title: Advanced Data Analytics Engineer Location:Chelsea, MI The Advanced Analytics Data Engineer develops, maintains, tests and evaluates data solutions. Responsibilities include but not limited to: β€’ Build what the Advanced Analytics Data Architect has designed. β€’ Work on implementing complex data projects with a focus on collecting, parsing, managing, analyzing and visualizing large sets of data to turn information into insights using multiple platforms. Requirements: β€’ Requires a Bachelor's degree in Computer Science, Information Technology, or related field. β€’ 3+ years of related experience required. β€’ MapReduce experience is a plus. β€’ SQL expertise and data modeling experience. β€’ Strong experience with Unix/Linux. β€’ ETL and data movement tools experience including: DataStage, Sqoop, and Pivotal Data Loader. β€’ Deep knowledge in data mining, machine learning, natural language processing, or information retrieval. β€’ Experience processing large amounts of structured and unstructured data. β€’ Knowledge of industry standard BA tools, including Cognos, QlikView, Business Objects, and other tools that could be used for enterprise solutions. β€’ Ability to tune Hadoop solutions to improve performance and end-user experience. β€’ Understanding of how algorithms work and have experience building high-performance algorithms. Key Must Have’s: β€’ Experience handling / processing large data sets both structured and unstructured β€’ Deep knowledge in data mining, information retrieval, and a natural curiosity about the data β€’ Expertise in data modeling specifically with less standardized / structured data