Designing, developing, and maintaining high-performance, scalable, and secure backend services and APIs using technologies such as Python and NodeJS.
Collaborating with science teams, full stack engineers, and data engineers to understand data requirements and integrate user needs into backend services.
Building and maintaining RESTful APIs to surface data in the platform, ensuring it is findable and accessible in line with FAIR principles.
Developing APIs that support future interoperability and federation for pathogen diagnostics, epidemiology monitoring, and research.
Working with data engineers to build pipelines and processes that store and transform platform data for easy consumption.
Implementing and managing data storage solutions including data lakes, data warehouses, and databases such as object storage, Oracle Autonomous Database, and PostgreSQL.
Supporting innovation efforts by exploring new technologies such as vector databases to enable search and AI use cases.
Using big data technologies like Kafka, Iceberg, and Parquet, along with managed databases including PostgreSQL and Oracle vector databases.
Operating, monitoring, and maintaining Oracle Cloud infrastructure to ensure backend services are highly available, scalable, and secure.
Collaborating with DevSecOps engineers to automate deployments and follow best-practice CI/CD.
Documenting and communicating APIs to engineers and bioinformaticians to support pipeline development and user-facing data products.
Promoting clean, standardized, maintainable, testable, and reusable code through technical standards.
Ensuring solutions are documented and aligned with architecture governance processes.
Implementing monitoring, logging, and alerting systems to maintain platform health and performance.
Line managing and supporting the development of a high-performing team of backend engineers focused on the data platform.
Requirements
**Essential knowledge, skills, and experience:**
Proven experience as a backend cloud engineer, data engineer, or similar role.
Proficiency in backend programming languages and API frameworks such as Python, NodeJS, Django, and FastAPI.
Experience building flexible APIs using GraphQL.
Expertise in at least one cloud platform and its managed data services.
Familiarity with big data technologies such as Parquet, Iceberg, and streaming platforms like Kafka.
Strong knowledge of database systems, SQL data model design, and query optimization.
Experience with containerization using Kubernetes and Docker.
Proven ability to deliver scalable and performant data services using microservice architectures.
Experience developing scalable architectures using containerized and serverless approaches such as Oracle Functions and AWS Lambda.
Team management experience and a track record of fostering a collaborative, high-performance culture.
Understanding of Agile methodologies and sprint-based workflows.
Commitment to knowledge sharing.
**Desirable knowledge, skills, and experience:**
Knowledge of genomics.
Experience with Oracle OCI.
Understanding of federation standards for genomics such as GA4GH.
Familiarity with healthcare clinical data and standards such as OMOP and SNOMED.
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