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Mid-level generalist data engineer title, metro location, and broad skillset drive high competition.
Strong SAP, MES, and enterprise data governance requirements limit cross-industry transferability.
Explicit 5–8+ years requirement plus mandatory SAP, SQL, Python, and integration platform experience increases strictness.
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Design, build, and operate scalable, secure enterprise data pipelines from SAP ECC/S4, Salesforce CRM, MES, and other sources.
Develop and manage enterprise data platforms (cloud data warehouses/lakes, SAP BW) enabling analytics, AI/ML, and reporting.
Implement data quality, governance, and security controls aligned with enterprise standards and support compliance audits.
Bachelor’s or Master’s degree in Computer Science, Engineering, Data Engineering, or related field.
5–8+ years of hands-on experience in data engineering with strong SAP data source expertise.
Proficiency in advanced SQL, Python, and Spark or equivalent data processing frameworks.
Experience working with enterprise integration platforms (e.g., MuleSoft, SAP BTP Integration Suite).
Experienced in implementing enterprise data governance and aligning master data across systems within SAP-centered enterprises.
Operational knowledge of building data pipelines integrating SAP, Salesforce, MES, and cloud platforms following enterprise architecture standards.
Skilled in data quality frameworks, DevOps/DataOps practices including CI/CD, infrastructure-as-code, and automated testing in a multi-region/global environment.