Our purpose is to deliver energy to the world, today and tomorrow. As a Staff Digital Twin Product Manager at bp, you will lead the strategy, development, and delivery of enterprise digital twin capabilities across global upstream assets. This role sits at the intersection of product management, data platforms, digital engineering, and asset operations, driving scalable, cloud-native digital twin platforms that deliver measurable outcomes across safety, reliability, efficiency, and cost.
This is a staff-level product leadership role, accountable not only for delivery, but for product adoption, platform sustainability, and realized business value. The role combines deep technical expertise in data modeling, contextualization, and integration with strong commercial foresight and cross-organizational influence.
Responsibilities:
- Define and own the product vision, roadmap, and value proposition for the Digital Twin platform and its core capabilities.
- Lead the strategy for data modeling, graph-based contextualization, and asset virtualization, supporting a wide range of operational and engineering use cases.
- Align product direction with enterprise priorities, including data platform simplification, automation, cost efficiency, and digital transformation.
- Partner with Product, Architecture, and Engineering to evolve digital twin capabilities for reuse across additional business areas.
Product Delivery & Execution:
- Own the end-to-end product lifecycle: conceptualisation, delivery, deployment, adoption, and continuous improvement.
- Lead Agile product delivery, including backlog prioritization, release planning, dependency management, and risk mitigation.
- Provide technical guidance and delivery leadership to squads, ensuring alignment across data, platform, and visualization workstreams.
- Supervise twin deployment, enhancement, and sustainment, ensuring solutions transition cleanly into operations.
Technical & Data Leadership:
- Act as the technical liaison between business and engineering, shaping solutions built on data architectures, including:
- Cloud-native data platforms (e.g., Databricks)
- Graph and contextual data models
- APIs and event-driven integrations
- SAP, ALIM, PI/IoT, engineering, and 3D data sources
- Lead the creation of a cost-effective, reliable, reusable digital twin platform supplying data to 1D / 2D / 3D / 4D visualization and analytics.
- Define and enforce data standards, governance, quality, and security frameworks.
- Coordinate data remediation and improvement plans with technology and data partners.
Collaborator & Customer Engagement:
- Engage directly with asset, engineering, and operational partners to:
- Understand use cases and data requirements
- Identify value opportunities and success measures
- Drive adoption and sustained usage
- Communicate roadmap progress, delivery plans, value realized, and costs to peers and senior leadership.
- Build strong, positive governance and collaboration models across product owners, product managers, and portfolio managers.
Value Realization & Commercial Competence:
- Identify, validate, and track benefits and value realization, including efficiency gains, cost reduction, and risk mitigation.
- Define and monitor product KPIs tied to adoption, performance, reliability, and business impact.
- Apply strong commercial judgment to prioritize initiatives that improve ROI and strategic value.
- Support cases, funding strategies, and investment decisions.
Required Qualifications:
- Bachelor's degree or equivalent experience in Engineering, Computer Science, Data Science, or related subject area.
- Strong experience in data, digital, or technology delivery in complex, global environments.
- Experience leading and developing teams, preferably with data or digital twin relevance.
- Deep understanding of:
- Data models, data standards, and contextualization
- Data integration, ETL, and transformation pipelines
- Cloud platforms (AWS, Azure)
- Strong business and domain knowledge from industrial or asset-intensive environments.
- Proven ability to lead through influence with strong collaborator engagement skills.
Preferred Experience:
- Digital Twin, asset virtualization, or industrial data platforms
- Graph technologies (e.g., Neo4j), big data ecosystems (Spark, Hive, Hadoop)
- Databricks, Python, and modern analytics platforms
- Delivery of data products at enterprise scale
Key Competencies:
- Strategic product thinking with strong execution bias
- Deep technical fluency across data and platform domains
- Commercial and business savvy
- Customer-centric, pragmatic mentality
- Strong communication and problem-solving skills
- Focus on value delivery with attention to detail
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