• Design and implement end-to-end data pipeline architecture spanning edge devices, ingestion, processing, storage, and delivery into analytics/AI workloads • Build scalable ETL and data processing frameworks with orchestration, schema management, versioning, and automated data quality controls • Develop real-time and streaming infrastructure supporting event-driven systems, edge-to-cloud synchronization, buffering strategies, and strict latency requirements • Own DevOps and infrastructure engineering, including CI/CD pipelines, infrastructure-as-code, container orchestration, and production deployment workflows • Implement and maintain security architecture across the stack, including access controls, secrets management, network segmentation, vulnerability scanning, and compliance practices • Establish strong observability, monitoring, and operational tooling for distributed systems running across cloud, edge, and enterprise integrations • Support onboarding of complex multimodal data sources including telemetry, time-series, video, audio, LiDAR, and geospatial datasets