Technical Project Manager for Healthcare AI Data Strategy & Operations

Requirements

• 5+ years of experience in technical project management, data operations, or a related field
• Demonstrated experience managing Healthcare data projects, with working knowledge of HIPAA, GDPR, PIPA, and othe

Benefits

Additional Information

Join us in pioneering breakthroughs in healthcare. For everyone. Everywhere. Sustainably. Our inspiring and caring environment forms a global community that celebrates diversity and individuality. We encourage you to step beyond your comfort zone, offering resources and flexibility to foster your professional and personal growth, all while valuing your unique contributions. We are seeking a Technical Project Manager to lead the execution of our data strategy for Healthcare AI. This role operates at the intersection of data engineering, AI/ML operations, and regulatory compliance, and is essential to responsibly scaling our data acquisition and data infrastructure across domestic and global teams. The Technical Project Manager will serve as the operational backbone of our data acquisition and processing pipelines. This includes coordinating closely with internal and external stakeholders, executing the data processing pipeline operations with our India team and interfacing with our data partners to ensure timely, high-quality data delivery. The role also carries responsibility for enforcing rigorous standards related to data privacy, regulatory compliance, security and quality while optimizing for cost efficiency, enabling sustainable and compliant growth of our Healthcare AI projects. You are responsible for: Data Strategy Execution Owning end-to-end project management for data strategy initiatives, translating organizational objectives into clear roadmaps, milestones, and executable delivery plans. Coordinating multi-source data acquisition efforts, including vendor negotiations, data ingestion oversight, and data quality validation activities. Establishing and maintaining comprehensive data lineage and provenance documentation across Healthcare AI data workflows to ensure traceability, transparency, and compliance. Partnering closely with Data Engineering and AI/ML teams to ensure data readiness for model development, training, validation, and deployment. Cross-Functional & Global Team Coordination Serving as the primary coordination lead between U.S.-based stakeholders and India-based operations and engineering teams, ensuring clear ownership, accountability, and effective collaboration. Leading structured alignment forums, including stand-ups, sprint reviews, and milestone check-ins, to maintain synchronization across distributed teams and time zones. Translating business objectives and technical requirements across functional, technical, and cultural boundaries. Identifying, communicating, and resolving delivery risks, blockers, cross-team dependencies, and resource constraints that may impact project timelines and outcomes. Compliance, Privacy & Governance Ensuring all data acquisition, processing, and storage activities comply with applicable regulatory and industry standards, including HIPAA, GDPR, PIPA, HL7 FHIR, FDA guidance, 510(k) submissions, and Predetermined Change Control Plans (PCCP). Maintaining and enforcing data governance frameworks encompassing data classification, access controls, retention schedules, and consent management practices. Supporting audit readiness efforts and coordinating responses to internal compliance reviews, SOC 2 audits, healthcare-specific certifications, and external vendor assessments. Collaborating closely with Legal, Information Security, and Compliance teams to proactively identify, assess, and mitigate privacy, security, and regulatory risks throughout the data lifecycle. Supporting Digital Technology & Innovation (DTI) initiatives related to Siemens Healthineers compliance requirements and governance standards. Scalability & Process Optimization Designing and implementing scalable, standardized workflows for data ingestion, transformation, and delivery to support growing data volumes and increasingly complex use cases. Identifying, prioritizing, and driving automation initiatives that reduce manual effort while preserving data quality, integrity, and end-to-end traceability, including developing automated workflows and workflow orchestration capabilities where appropriate. Defining, tracking, and optimizing key performance indicators for data operations, including throughput, latency, error rates, data quality metrics, and compliance-related measures. Cost Management Owning budgeting, financial planning, and spend tracking for data acquisition contracts, cloud-based infrastructure, and supporting tools and platforms. Analyzing key cost drivers and identifying optimization opportunities across storage, compute, data ingestion, and external vendor expenditures. Providing regular cost forecasts, variance analyses, and financial reporting to ensure data operations scale efficiently, sustainably, and responsibly.

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