Principal Software Engineer – Microscopy Data Management & Cloud Platform

Job Description

• This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Principal Software Engineer – Microscopy Data Management & Cloud Platform based in India. This is a hands-on principal engineering role focused on building a distributed scientific data platform for microscopy and life-science applications. You will design systems capable of managing large-scale image data, metadata, search, transformation, storage, transfer, and analysis workflows. The platform will operate across laboratory instruments, user devices, on-premise environments, and AWS cloud infrastructure. You’ll tackle complex challenges around high-throughput data pipelines, reliable transfers, database architecture, and distributed multi-user systems. The role combines deep technical execution with architectural leadership, influencing engineering standards and cross-team technical direction. You’ll collaborate closely with specialists across image analysis, instrument software, web applications, cloud engineering, and scientific domains. This is a fully remote opportunity in India with significant scope to shape a platform supporting advanced scientific and life-science workflows.
• Accountabilities: Design and develop a distributed data management platform supporting microscopy, scientific imaging, and life-science workflows. Architect scalable storage, indexing, search, caching, and high-throughput data-transfer mechanisms for large scientific datasets across hybrid edge, on-premise, and cloud environments. Design and implement robust backend APIs, contracts, schemas, and interfaces that enable interoperability between instrument control systems, image-analysis applications, user interfaces, and cloud services. Build reliable and resumable data-transfer pipelines between instruments, local systems, and cloud environments, including solutions for offline-first and intermittently connected scenarios. Develop high-performance data ingestion, streaming, and transformation pipelines for large microscopy datasets and associated metadata. Establish mechanisms for data integrity, consistency, traceability, versioning, reproducibility, checksums, validation, and auditability. Contribute to database architecture, data lifecycle management, query performance, indexing strategies, and scalable data-access patterns. Collaborate with image-analysis teams, web UI engineers, instrument software developers, and scientific domain experts to define robust interfaces and end-to-end workflows. Contribute to engineering standards covering CI/CD, observability, reliability, security, and cloud-based as well as instrument-hosted software delivery. Provide technical leadership through architectural decisions, hands-on implementation, design reviews, technical problem-solving, and cross-team alignment. Mentor engineers and help establish scalable engineering practices for complex distributed systems. Evaluate emerging technologies and approaches that can improve data discovery, scientific workflows, platform scalability, and system performance. Requirements: Master’s degree in STEM or equivalent practical experience. 10+ years of software engineering experience, including significant experience designing complex distributed backend systems or data platforms. Strong hands-on 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 designing backend APIs using REST and/or gRPC, including contract versioning, backward compatibility, and interface governance. Solid understanding of network protocols and performance optimization, including HTTP/2, gRPC, TCP/IP behavior, latency, throughput, and network-performance trade-offs. Experience designing asynchronous and event-driven architectures using message queues, streaming systems, or comparable technologies. Proven understanding of data-integrity mechanisms such as checksums, hashing, validation, and consistency models. Strong experience designing AWS-based backend systems, cloud storage, compute infrastructure, and scalable services. Excellent architectural thinking, system decomposition, troubleshooting, and performance-optimization capabilities. Experience with scientific or imaging data systems, microscopy, digital imaging, laboratory software, or scientific data pipelines is highly desirable. Familiarity with microscopy metadata, OME concepts, scientific image formats, tiled or multiresolution imagery, and image-processing workflows is an advantage. Experience designing search and discovery solutions for complex metadata and large datasets is beneficial. Knowledge of secure multi-user systems, authentication, authorization, auditability, and identity platforms such as Keycloak or LDAP/Active Directory is a plus. Experience with S3-compatible object storage, hybrid deployments, and on-premise/cloud synchronization is desirable. Familiarity with Docker, Kubernetes, Terraform, C++, Bash, or PowerShell is advantageous. Exposure to vector search, AI/ML data retrieval patterns, life-science ontologies, scientific data standards, or regulated/quality-driven environments is a plus. Strong communication and collaboration skills, with the ability to influence technical direction across multiple engineering and scientific teams. Benefits: Full-time, fully remote position based in India. Opportunity to work on advanced scientific data-management and microscopy platforms with real-world applications in life sciences. Significant technical ownership across distributed systems, cloud architecture, data engineering, and backend platform design. Opportunity to influence architecture, engineering standards, reliability, security, and platform strategy at a principal level. Collaboration with multidisciplinary teams spanning software engineering, cloud, scientific imaging, instrumentation, and data analysis. Exposure to AWS, large-scale scientific datasets, hybrid cloud/on-premise environments, and modern distributed-system technologies. Opportunities to mentor engineers, shape technical practices, and contribute to complex, high-impact engineering initiatives.
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