Data Architect (m,kn,)

We are looking for an experienced Senior Data Architect / Engineering Lead to design and build the data foundation for emerging technology programs. This role combines strategic architecture ownership with hands-on engineering delivery across complex, multi-source environments.

• Proven experience in data architecture and data engineering within complex, multi-source environments and Data Architect role
• Strong hands-on experience building modern data pipelines and integration frameworks
• Experience with cloud-based data platforms and distributed data processing
• Strong knowledge of batch, streaming, and event-driven architectures
• Experience with operational and analytical data modeling
• Experience integrating machine, device, telemetry, or operational data into enterprise platforms
• Strong understanding of APIs, interoperability, and integration patterns
• Ability to operate as both architect and hands-on delivery lead
• Excellent communication skills across technical and business stakeholders

Preferred Qualifications:

• Experience in frontier technology, industrial, infrastructure, advanced engineering, or innovation-driven environments
• Familiarity with edge-to-cloud architectures, digital twins, simulation data, or AI-ready platform design
• Experience with metadata management, lineage, and governance integration
• Experience working in regulated, operationally sensitive, or multi-party ecosystems

• Define and own end-to-end data architecture across source systems, streaming pipelines, storage, transformation layers, APIs, and consumption platforms
• Design and implement scalable data pipelines for structured, semi-structured, unstructured, and real-time data
• Integrate data from enterprise applications, devices, sensors, operational systems, third-party providers, and partner ecosystems
• Establish canonical data models and integration patterns across assets, events, locations, products, devices, users, and operational processes
• Collaborate with security and governance teams to ensure access control, lineage, quality, and compliance requirements are embedded into the architecture
• Support real-time and near-real-time ingestion and processing use cases
• Drive interoperability across fragmented technical and business environments
• Establish engineering standards, DataOps practices, monitoring, and reliability controls
• Enable downstream analytics, AI, simulation, and scalable data product consumption
• Provide technical leadership across platform decisions, implementation sequencing, and delivery trade-offs