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Tier-1 brand, remote work, generalist Data Engineer title, and metro location create high applicant competition.
Data engineering skills transfer well, but SAP/ERP focus raises domain specificity to medium.
Many mandatory technologies and scripting requirements create high shortlisting strictness.
Develop and support creation of structured data models and reusable data sets for analytical use, including management, operational, predictive, and data science applications.
Design, develop, and maintain scalable ETL processes and data migrations across various enterprise systems (e.g., MS Dynamics, Oracle, SAP).
Participate in testing, validation, and documentation of data transformations and assist in defining data requirements and prioritization for change initiatives.
Bachelor's degree in computer science, software engineering, IT, or related field.
Moderate experience in data engineering and data mining within fast-paced environments, including building analytics solutions with large multi-terabyte data sets.
Proficiency with Microsoft Azure Data Factory, SQL Analysis Server, SAP Data Services, SAP BTP, and scripting languages like Perl, Python, Shell scripting.
Experience with big data tools (Hadoop, Cassandra, Storm), databases (SAP, SQL, MySQL, Microsoft SQL), and moderate programming experience in .NET or applicable languages.
Experienced in designing scalable and secure data architectures and ETL pipelines in enterprise environments with multi-source ERP integrations.
Capable of handling complex data migrations, testing, and validation processes, paying attention to accuracy and adhering to installation and design standards.
Skilled in programming and automation with a focus on scripting (Perl, Python, shell) to support data engineering tasks and improve process efficiency.