Principal Software Engineer – Microscopy Data Management & Cloud Platform

Role Summary We are looking for a hands-on Principal Software Engineer to design and implement a distributed scientific data platform for microscopy and life-science applications. The platform must support microscopy image data, metadata, search, transformation, storage, transfer and analysis workflows across instruments, user PCs, on-premise deployments and AWS cloud environments. This role requires deep expertise in database-centric system design, high-throughput data pipelines, reliable data transfer protocols, backend interface design and scalable multi-user distributed systems. You will - Contribute to the design and development of a distributed data management platform for microscopy and scientific imaging workflows. - Design scalable storage, indexing, search, caching and high-throughput data-transfer mechanisms for large scientific datasets in hybrid edge/on-prem/cloud environments. - Design and implement robust backend interfaces (APIs, contracts, schemas) enabling interoperability across platforms (instrument control, image analysis, UI, cloud services). - Design and implement reliable and resumable data transfer pipelines between instruments, local systems and cloud (including offline-first and intermittent connectivity scenarios). - Develop high-performance data ingestion, streaming and transformation pipelines for large image datasets and metadata. - Define and implement data consistency, integrity and traceability mechanisms (checksums, versioning, audit trails, reproducibility). - Collaborate with image analysis, web UI, instrument software and domain experts to define robust interfaces and end-to-end workflows. - Contribute to engineering standards, CI/CD, observability, reliability and secure software delivery for cloud-based and instrument-hosted systems. - Provide technical leadership through architecture decisions, hands-on implementation, design reviews, mentoring and cross-team alignment. Must have - MS in STEM or equivalent practical experience - 10+ years in software engineering, including design of complex distributed backend or data platforms. - Strong programming skills in Python and C#. - Deep expertise in database design, schema evolution, query optimization, transactions, indexing, data security and data lifecycle management. - Strong experience in backend API design (REST/gRPC), contract versioning, backward compatibility and interface governance. - Understanding of network protocols and performance tuning (HTTP/2, gRPC, TCP/IP behavior, latency vs throughput trade-offs). - Experience with asynchronous and event-driven architectures (message queues, streaming systems). - Experience with data integrity mechanisms (checksums, hashing, validation, consistency models). - Proven experience with AWS-based backend systems, storage, compute and scalable service design. - Strong architectural thinking, system decomposition and performance optimization skills. Nice to have - Experience with scientific or imaging data systems, ideally microscopy, digital imaging or laboratory software. - Experience with microscopy image metadata, OME concepts, image file formats, tiled or multiresolution image handling or scientific imaging pipelines. - Experience designing search solutions for complex metadata and dataset discovery. - Experience building secure multi-user systems with authentication, authorization and auditability. - Experience with S3-compatible object storage, hybrid deployments and on-prem/cloud synchronization. - Experience with caching, asynchronous workflows, data pipelines and event-driven architectures. - Experience with regulated or quality-driven environments. - Experience with access control integration, Keycloak, LDAP/AD or customer-specific identity systems. - C++/Bash/PowerShell - Docker/Kubernetes/Terraform - Vector search or AI/ML data retrieval patterns - Experience with life-science ontologies and scientific data standards