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Strong employer brand, popular data engineer role, unspecified experience, and metro location increase competition.
Requires enterprise ERP and Azure/big-data tool experience, making cross-industry transferability moderately constrained.
Extensive mandatory enterprise data stack and 'seasoned' expertise requirements imply strict technical filtering.
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Develop and maintain data models and scalable ETL processes to support business analytics including management, operational, predictive, and data science capabilities.
Responsible for data transformation, migration across systems such as MS Dynamics, Oracle, SAP, and ensuring data accuracy through testing and validation.
Collaborate with IT and business teams to define data requirements, design database schemas, and recommend improvements to data queries and models.
Bachelor's degree or equivalent in computer science, software engineering, information technology, or related field.
Seasoned experience in data engineering, data mining, and building modern data analytics solutions with multi-terabyte scale data sets.
Strong proficiency in Microsoft Azure Data Factory, SQL Analysis Services, SAP Data Services, SAP BTP, and scripting languages such as Perl, Bash, Shell Scripting, Python.
Experience with big data tools (Hadoop, Cassandra, Storm), databases (SAP, SQL, MySQL, Microsoft SQL), and automation of data processes.
Experienced in designing secure, highly available, and scalable data systems with strong understanding of physical and logical data modeling.
Able to manage scoping, requirements definition, and prioritization for data-related projects and changes.
Skilled in collaborating across multiple teams and communicating effectively to align data architecture with business analytics needs.