Senior Manager Data Engineering

• Define 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 end-to-end data pipelines ensuring data accuracy, performance, and scalability across the reporting ecosystem
• Strategize and recommend AI-enabled solutions that improve data quality, reduce manual effort, and accelerate insight delivery for the reporting domain
• Drive automation of manual reporting processes, reduce cycle times, and improve operational efficiency across the reporting lifecycle
• Establish and enforce data quality frameworks, governance models, and monitoring standards across all reporting data assets
• Lead the transition from legacy to modern cloud-based architectures, ensuring seamless migration with minimal disruption
• Mentor and guide a team of junior resources and drive delivery, establish best practices, and build a culture of innovation and continuous improvement

• Partner with product management, business analysts, and stakeholders to translate business requirements into scalable data and AI solutions

• Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so

Required Qualifications:

• Undergraduate degree or equivalent experience
• 10+ years in Data Engineering with at least 3+ years in a technical lead or senior individual contributor role
• 3+ years of hands-on AI/ML experience - building, training, and deploying models in real-world environments
• Hands-on experience with large-scale data pipeline development, data modeling, and data warehousing
• Practical experience in applying AI/ML techniques to solve business problems - classification, prediction, automation, or intelligent search
• Experience working with Large Language Models (LLMs) and building AI-powered applications using modern AI frameworks and tools
• Experience with data migration - transitioning from legacy systems to modern cloud-based architectures
• Solid expertise in Python, SQL, and cloud-based data engineering platforms (Azure preferred)
• Demonstrated ability to lead and mentor engineering teams with hands-on coaching and technical direction
  • Demonstrated excellent communication skills - ability to present technical solutions clearly to business stakeholders and leadership