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Utilizes software engineering principles to deploy and maintain fully automated data transformation pipelines that combine a large variety of storage and computation technologies to handle a distribution of data types and volumes in support of data architecture design.
Utilizes software engineering principles to deploy and maintain fully automated data transformation pipelines that combine a large variety of storage and computation technologies to handle a distribution of data types and volumes in support of data architecture design.
Responsibilities include:
Understand business use of data and stakeholder requirements to support work processes and strategic business objectives
Leverage data, software engineering, and data science techniques to create business value through data accessibility. Includes data ingestion, data preparation and analytics processing.
Identify, acquire, cleanse & prepare, store data and develop data products aligned with defined architecture patterns
Responsible for normalizing and ingesting data from multiple sources.
Enable data scientists, making data available for advanced analytics models, and contributing to models.
Work with ML Engineer to scale and deploy solution including model, documentation, training, integration
Contributing to the inner source development of foundational tools, and/or the deployment of technical services.
Required Qualifications:
BS in Computer Science, Management Information Systems, Computer Engineer or related fields or equivalent experience.
+5 years in Data Engineer Role
Knowledge and/or experience with: data acquisition, preparation and validation; data movement and transformation; analytics solution architecture; big data computing; cloud computing, core data architecture; information security technologies and software engineering using technologies such as: Azure Data Factory (ETL), Databricks, DevOps, CI/CD Pipeline Deployment, Python, Java, Ansible, Azure SQL, Azure Synapse, GIT, ADO, Azure Data Lake, Azure Analysis Services, Logic Apps, Microsoft Data Flows, Kimball Data Warehousing Methodology
Analytical thinking, Consulting, Critical Thinking
Relocation Options:
Relocation may be considered.
International Considerations:
Expatriate assignments will not be considered
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