Principal Software Engineer - Microscopy Data Management and 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