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Tier-1 employer and metro hiring increase competition, but seniority and niche ML/data expectations limit candidate pool.
Technical data engineering and healthcare reporting focus requires domain experience, but core skills remain transferable.
Multiple explicit mandates: 10+ years, leadership experience, hands-on ML, and Azure/Python/SQL technical requirements.
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Own and execute the data engineering and AI strategy for NICE Reporting, including data sourcing, pipeline architecture, automation, and migration to modern reporting platforms.
Design, develop, and optimize scalable, high-performance data pipelines ensuring data accuracy across the reporting ecosystem.
Lead migration from legacy to cloud-based architectures and mentor a team to drive delivery, innovation, and best practices.
Undergraduate degree or equivalent experience.
10+ years of experience in Data Engineering, including at least 3 years in a technical lead or senior individual contributor role.
3+ years of hands-on AI/ML experience, including building and deploying models.
Proficiency in Python, SQL, cloud-based data engineering platforms (Azure preferred), and experience with data migration and AI-powered applications.
Experienced in leading and mentoring data engineering teams with hands-on technical coaching and clear communication to stakeholders.
Strong expertise applying AI/ML techniques to business problems, including experience with Large Language Models and modern AI frameworks.
Proven track record managing large-scale data pipelines and migrating legacy systems to cloud architectures in a reporting or analytics environment.