R&D Data Platform Lead

Qcells is seeking an R&D Data Platform Lead to architect, build, and scale the R&D data platform across global sites and systems. The role connects R&D environments - equipment, lab systems, process data, experiments, and documents - into a trusted, scalable data foundation that supports analytics, reporting, and AI capabilities.

You will work closely with global R&D teams, Digital Transformation, Information Security, IT, and external partners to define strategy and deliver reliable platform infrastructure., * Lead technical architecture, roadmap, and implementation priorities for the R&D data platform.

• Design and build scalable data pipelines across equipment, process, lab, material, and document data sources.
• Translate R&D and business requirements into reusable data models, integration patterns, and platform components.
• Evaluate and recommend cloud platforms, databases, ETL/ELT tools, and analytics environments.
• Ensure platform supports data quality, lineage, metadata, access control, and governance requirements.
• Establish AI-ready data foundations to enable search, analytics, and ML use cases over R&D data.
• Align platform strategy with R&D, DT, IT, security, and regional site stakeholders.
• Partner with external consultants and HQ technical teams for proof-of-concept and scale-up.
• Own platform documentation, monitoring, and long-term maintainability beyond individual vendor engagements.

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field.
• 6+ years of experience in data engineering, data architecture, or cloud data platform development, including demonstrated ownership of a platform initiative from design through delivery.
• Hands-on experience designing data pipelines, ETL/ELT processes, and data models.
• Strong knowledge of SQL, APIs, data modeling, and modern data platform architecture.
• Experience working across technical and business stakeholders in a matrix organization.
• Strong communication and problem-solving skills; able to translate between technical and business needs., * Experience in R&D, manufacturing, solar, semiconductor, materials science, or industrial automation environments.
• Familiarity with Azure, Databricks, Microsoft Fabric, Snowflake, or similar platforms.
• Experience with equipment data, MES, lab systems, or experimental/reliability data.
• Exposure to AI/ML, advanced analytics, or digital transformation programs.

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