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Data Program Manager

Job in Santa Clara, Santa Clara County, California, 95053, USA
Listing for: Siemens Mobility
Full Time position
Listed on 2026-10-11
Job specializations:
  • IT/Tech
    AI Business & Operations, Business Systems & Technology Analysis, Change Management
  • Business
    AI Business & Operations, Business Systems & Technology Analysis, Change Management
Salary/Wage Range or Industry Benchmark: 129000 - 172000 USD Yearly USD 129000.00 172000.00 YEAR
Job Description & How to Apply Below
  • Santa Clara
    - California
    - United States of America

Here at Siemens, we take pride in enabling sustainable progress through technology. We do this through empowering customers by combining the real and digital worlds. Improving how we live, work, and move today and for the next generation! We know that the only way a business thrives is if our people are thriving. That’s why we always put our people first.

Our global, diverse team would be happy to support you and challenge you to grow in new ways. Who knows where our shared journey will take you?

We are building intelligent systems that bring generative AI into the physical world - merging models, embodiment, and real-time perception into entirely new product experiences. As a Data Program Manager are responsible for all aspects of data acquisition for the next generation of AI products by working on cross-functional DAI (data and artificial intelligence) data programs that support Siemens’ AI and industrial AI initiatives.

Here you will partner with applied science, product, engineering, and operations to design and implement pragmatic solutions for acquiring data. You will be a key interface between our product roadmap and external data offerings. The role will own multiple related work streams and serve as a liaison across Product, Engineering, Applied Science, Legal, Compliance, Procurement, and external data partners. The Data Program Manager will translate business and product needs into executable data programs, establish operating mechanisms, manage dependencies and risks, and drive programs through delivery.

Key responsibilities
  • Manage complex, cross-functional AI data programs and interconnected work streams from planning through delivery, aligning evolving requirements with clear objectives , milestones, and operating plans.
  • Drive execution across Product, Engineering, Applied Science, Legal, Compliance, Procurement, Security, and other stakeholders, while representing programs in leadership forums.
  • Oversee end-to-end data acquisition, annotation, curation, licensing, and readiness, and manage strategic day-to-day relationships with internal and external data owners
  • Establish success metrics, requirements, and acceptance criteria for data deliverables to measure progress, quality, readiness, and compliance with organizational policies.
  • Identify systemic risks, resolve complex cross-organizational dependencies, and lead regular program reviews to communicate status and decisions to senior leadership.
  • Manage budgets, resource planning, and vendor commitments while developing scalable governance models, templates, and operating processes to improve program efficiency.
Basic Qualifications
  • Bachelor’s degree or equivalent practical experience.
  • 4+ years of experienc in program management, project management, operations, technology programs, data programs, or a related field .
  • Demonstrated experience independently leading complex, cross-functional programs.
  • Experience managing multiple work streams, dependencies, stakeholders, and external partners.
  • Excellent written and verbal communication skills, including communication with senior stakeholders.
  • Strong analytical, organizational, and problem-solving skills.
Preferred Qualifications
  • Experience managing AI, data, software, or technology programs.
  • Experience with data acquisition, data annotation, data curation, or data lifecycle programs.
  • Experience developing and executing data acquisition strategies that leverage frontier AI models for data discovery, generation, enrichment, transformation, and quality evaluation, with an understanding of when to apply AI-driven approaches versus traditional or human-in-the-loop methods.
  • Familiarity with data governance, data privacy, licensing, or responsible AI…
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