Program Manager, PIC Data Engineering

Nokia is seeking an experienced Program Manager, PIC Data Engineering to lead the development of scalable, secure, and governed data platforms for photonic integrated circuit operations. The role focuses on data architecture, pipelines, governance, AI-ready foundations, operational excellence, and leadership of product engineering teams.

Responsibilities:

• Strategic Data Architecture: Lead the architectural design and hands-on implementation of cutting-edge, scalable cloud-based lakehouse and data warehouse solutions in PICs operation, primarily leveraging Databricks and AWS or alike to support Nokia's evolving operation data needs
• Data Model Evolution: Drive the design, optimization, and evolution of enterprise data models and semantic layers, ensuring they are robust, future-proof, and aligned with business objectives
• High-Performance Data Pipelines: Engineer, build, and maintain resilient, high-performance batch and real-time data pipelines, encompassing advanced ETL/ELT and streaming solutions to deliver timely and accurate data
• Data Trust & Quality: Establish and champion comprehensive data quality frameworks, monitoring, and observability practices to ensure the integrity, reliability, and trustworthiness of our data assets
• Operational Excellence: Implement CI/CD pipelines and DataOps best practices, fostering automation, reliability, and secure deployment across our data ecosystem
• Enterprise Data Governance: Spearhead the implementation of robust enterprise data governance standards, including data cataloging, lineage, metadata management, and stringent data access controls
• Security by Design: Design and enforce strong security protocols and role-based access management across all enterprise data platforms, safeguarding sensitive information
• AI-Ready Data Foundations: Build governed, AI-ready data foundations that empower self-service analytics, AI-assisted data exploration, and advanced analysis, leveraging capabilities such as Databricks Genie and Genie Code
• Empowering Data Users: Enable business, engineering, and analytics teams to securely access trusted enterprise data, fostering conversational analytics and AI-assisted analysis while upholding stringent governance, security, and data quality standards
• Innovation Catalyst: Develop the foundational data infrastructure essential for pioneering AI, automation, machine learning, and advanced analytics initiatives that drive Nokia's competitive edge
• Team Leadership & Mentorship: Lead, mentor, and inspire a high-performing team of product engineers, setting technical standards, promoting engineering best practices, and fostering continuous professional growth
• Culture of Excellence: Champion a culture of data excellence, accountability, self-service enablement, and continuous innovation within the organization

Requirements:

• 15+ years of progressive experience in data engineering, data architecture, or related fields, with a proven track record of delivering impactful solutions in wafer and chip fabrication process
• Bachelor's degree
• 5+ years of experience leading, developing, and inspiring technical teams, fostering a collaborative and high-achieving environment
• Deep expertise in SQL, modern cloud data platforms, and distributed data processing frameworks
• Hands-on experience with leading cloud data platforms such as Databricks, Redshift, or BigQuery
• Demonstrated experience in building governed data platforms and data products that effectively support self-service analytics, AI-assisted analytics, machine learning, and advanced analytical workloads
• Strong understanding of enterprise data modeling principles, including dimensional modeling and semantic layers
• Experience with data orchestration tools and advanced data pipeline automation techniques
• Proven ability to design and implement scalable, secure, governed, and reliable enterprise data solutions
• Exceptional communication and interpersonal skills, with a proven ability to partner cross-functionally with business, engineering, analytics, and technology teams to drive shared success
• Master's degree
• Experience with Databricks capabilities, including lakehouse architecture, Unity Catalog, and AI-assisted analytics features like Genie and Genie Code