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Tier-1 brand, remote work, common mid-level data engineer title, and metro location drive high competition.
Platform-specific SAP/Azure and enterprise data tool requirements moderately limit cross-industry transferability.
Multiple mandatory platform and tooling requirements increase filtering despite no explicit years threshold.
Develop and maintain structured data models and ETL packages to support business analytics requirements including operational and predictive capabilities.
Support data migrations across various databases and ERP systems like MS Dynamics, Oracle, SAP.
Create and validate test scenarios to ensure accuracy of data transformations and contribute to documentation for ETL and migration processes.
Bachelor's degree in computer science, software engineering, information technology, or related field.
Moderate experience in data engineering, data mining in fast-paced environments with familiarity in multi-terabyte data sets.
Experience with Microsoft Azure Data Factory, SQL, SAP Data Services, and scripting languages such as Perl, Bash, Shell Scripting, Python.
Work Experience Required: Moderate level experience explicitly mentioned in data engineering and related activities.
Experienced in designing and managing scalable, secure, and highly available data architecture and analytics solutions.
Proficient in scripting/automation and big data tools including Hadoop, Cassandra, Storm, with experience in .NET preferred.
Able to work remotely and engage with multiple stakeholders to translate business analytics needs into data models and ETL workflows.