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Recognized global firm, popular mid-level data engineer title, and metro hiring drive high competition.
Data engineering skills are broadly transferable across industries despite the healthcare domain context.
Explicit 4+ years plus mandatory Python/SQL and production-support requirements make shortlisting strict.
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Manage and own data transfer processes including setup and onboarding of contributors and customers.
Design, develop, maintain, and support Python-based data pipelines, workflows, and automation focusing on operational support.
Provide production support including monitoring, troubleshooting, incident management, and continuous process improvement with AI-enabled approaches.
4+ years of experience in Data Engineering or Data Management with production pipeline support.
Bachelor’s degree in Engineering, Computer Science, or related field, or equivalent practical experience.
Strong proficiency in Python for data pipelines, automation, and operational tooling.
Proficiency in SQL, data manipulation, automation frameworks, and knowledge of AI-assisted techniques and Agile methodologies.
Experienced in supporting production-level data engineering systems with incident and service recovery expertise.
Able to collaborate across technical stakeholders and translate product requirements into scalable data solutions.
Comfortable working in Agile environments using diverse platforms such as Windows, Unix, and HPCC with emphasis on automation and AI-driven improvements.