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Sr Principal Program Mgr, PIC Data Eng

Nokia
Remote, USA
Full-time
Senior · 15+ years experience
Remote
Discovered 1 weeks ago
bigquerydatabricksredshiftsql

Full Job Posting

Qualifications

  • Extensive Experience: 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.
  • Education: Bachelor's degree. Master's degree preferred.
  • Leadership Acumen: 5+ years of experience leading, developing, and inspiring technical teams, fostering a collaborative and high-achieving environment.
  • Technical Mastery: Deep expertise in SQL, modern cloud data platforms, and distributed data processing frameworks.
  • Cloud Data Platform Proficiency: Hands-on experience with leading cloud data platforms such as Databricks, Redshift, or BigQuery.
  • Governed Data Platforms: 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.
  • Databricks Ecosystem (Preferred): Experience with Databricks capabilities, including lakehouse architecture, Unity Catalog, and AI-assisted analytics features like Genie and Genie Code, is highly preferred.
  • Data Modeling Expertise: Strong understanding of enterprise data modeling principles, including dimensional modeling and semantic layers.
  • Orchestration & Automation: Experience with data orchestration tools and advanced data pipeline automation techniques.
  • Scalability & Reliability: Proven ability to design and implement scalable, secure, governed, and reliable enterprise data solutions.
  • Collaborative Communication: Exceptional communication and interpersonal skills, with a proven ability to partner cross-functionally with business, engineering, analytics, and technology teams to drive shared success.

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.

Preferred Qualifications

  • Education: Bachelor's degree. Master's degree preferred.
  • Databricks Ecosystem (Preferred): Experience with Databricks capabilities, including lakehouse architecture, Unity Catalog, and AI-assisted analytics features like Genie and Genie Code, is highly preferred.

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