Program Manager, PIC Data Engineering

Nokia•United States,

12h

About The Position

At Nokia, we are shaping the future of connectivity and innovation. We are seeking a visionary and experienced Program Manager, PIC Data Engineering, to lead the development of our next-generation data platforms, driving strategic insights and enabling AI-powered solutions across our global enterprise for photonic integrated circuit (PICs) technology. This role is critical in building the robust, secure, and scalable data foundations that underpin Nokia's digital transformation and technological leadership.

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. Master's degree preferred.
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.

Nice To Haves

Experience with Databricks capabilities, including lakehouse architecture, Unity Catalog, and AI-assisted analytics features like Genie and Genie Code, is highly preferred.

Responsibilities

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.
Drive the design, optimization, and evolution of enterprise data models and semantic layers, ensuring they are robust, future-proof, and aligned with business objectives.
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.
Establish and champion comprehensive data quality frameworks, monitoring, and observability practices to ensure the integrity, reliability, and trustworthiness of our data assets.
Implement CI/CD pipelines and DataOps best practices, fostering automation, reliability, and secure deployment across our data ecosystem.
Spearhead the implementation of robust enterprise data governance standards, including data cataloging, lineage, metadata management, and stringent data access controls.
Design and enforce strong security protocols and role-based access management across all enterprise data platforms, safeguarding sensitive information.
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.
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.
Develop the foundational data infrastructure essential for pioneering AI, automation, machine learning, and advanced analytics initiatives that drive Nokia's competitive edge.
Lead, mentor, and inspire a high-performing team of product engineers, setting technical standards, promoting engineering best practices, and fostering continuous professional growth.
Champion a culture of data excellence, accountability, self-service enablement, and continuous innovation within the organization.