Oxenham Group

Data Engineer

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Engineer with a contract length of "unknown," offering a pay rate of "unknown." Required skills include 3-5 years of experience in Data Engineering, proficiency in Azure Synapse Analytics, Azure Data Factory, and SQL Server.
🌎 - Country
United States
πŸ’± - Currency
$ USD
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πŸ’° - Day rate
520
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πŸ—“οΈ - Date
May 15, 2026
πŸ•’ - Duration
Unknown
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🏝️ - Location
Unknown
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πŸ“„ - Contract
Unknown
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πŸ”’ - Security
Unknown
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πŸ“ - Location detailed
Indiana, United States
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🧠 - Skills detailed
#Data Engineering #Azure #Data Warehouse #"ETL (Extract #Transform #Load)" #Azure Synapse Analytics #SQL Server #Agile #IoT (Internet of Things) #Databases #SQL (Structured Query Language) #ADF (Azure Data Factory) #Azure Data Factory #Synapse #MLOAD (MultiLoad)
Role description
Our customer is a global IoT manufacturer. The company is hiring a data engineer to support existing Data Warehouse & Lakehouse initiatives for the data engineering team. This role will collaborate with the Global Data & Analytics Team, designing, and rolling out technical solutions. Responsibilities β€’ Collaborate with Global Data Team Members to review requirements & translate to ELT design and implementation. β€’ Understand Extract Transform and Load technical approaches and designs. β€’ Understand the agile approach, leveraging best practices and implementing/documenting repeatable processes. β€’ Coordinate with all source-system, and IT teams to ensure integration points are managed and involved. β€’ Perform technical validation of extracted data. β€’ Support & Maintain Global Data Assets. Requirements: β€’ Bachelor’s Degree in a related field OR Technical Certification equivalent. β€’ 3-5 Years’ experience in Data Engineering and Analytics. β€’ Execute and deliver with agile / iterative approach. β€’ Experience working with Azure Synapse Analytics, Azure Data Factory, or Extract-Transform-Load Tool equivalent. β€’ Experience working with SQL Server Databases.