Evaluate, recommend, and introduce modern data technologies and patterns (e.g., cloud‑native services, orchestration frameworks, feature‑ready datasets) aligned with Materials Discovery’s current and future needs while proactively addressing system limitations, scaling risks, and performance bottlenecks. Design, build, and evolve data architectures and ETL/ELT pipelines to collect, process, and store data from diverse sources (e.g., laboratory systems, databases, APIs, and external data providers), ensuring data accuracy, completeness, reproducibility, and timeliness.