Information Technology Specialist - Data & Platform Integration

The International Water Management Institute (IWMI), a CGIAR Research Center, is on the lookout for a versatile professional to join its headquarters in Battaramulla, Sri Lanka, as an Information Technology Specialist – Data & Platform Integration. The Information Technology Specialist designs, integrates, and operates data pipelines, APIs, and application workflows that support IWMI’s research platforms and AI enabled services. The role translates research and business requirements into scalable, secure, and standards compliant technical solutions, working closely with researchers, platform engineers, and service providers. It ensures data quality, governance, operational reliability, and effective integration of research outputs into production platforms. DUTIES & RESPONSIBILITIES:Main Purpose of Job: • Application and Integration, • Plan, design, and deliver geospatial data integration solutions and application workflows that meet end‑user and stakeholder requirements, including software, programs, and databases. • Design and maintain standardized data schemas, ingestion protocols and database architectures that aligned with pre-approved standards that meet functional needs, scalability, and maintainability objectives.

• Architecture, Data and AI, • Evaluate application, data and cloud architectures to ensure alignment with functional requirements, performance, scalability, and organizational goals. • Develop, customize and enhance data pipelines, ETL (Extract, Transform, Load) workflows and API integrations using approved technologies to facilitate interoperable, scalable, and maintainable application and data architectures that meet functional needs, scalability, and maintainability objectives. • Ensure data quality stewardship and integrity by implementing scheme validation, quality checks, versioning controls and lineage documentation across research and platform data pipelines. • Oversee data storage and retrieval processes and safeguard data integrity, security and compliance by applying data governance standards, access controls, retention policies, FAIR data principles, and country‑specific data residency requirements.

Main engagement, collaboration and communication responsibilities: • Application and Integration, • Translate team requirements into technical specifications for data integration, application workflows and API services, acting as a technical liaison between researchers, platform engineers, and service providers. • Collaborate with platform engineering teams and external service providers to ensure data integration, API, and infrastructure deliverables meet agreed technical specifications and standards.

• Architecture, Data and AI, • Participate in sprint reviews, architecture design sessions, technical meetings and deployment readiness activities as data integration authority to align deployments with business schedules and minimize disruption. • Coordinate with AI, data and platform teams to ensure integration of research outputs into AI‑enabled services and RAG repositories in compliance with institutional AI security, ethics, and governance standards. • Engage with IWMI researchers to review and provide structured technical feedback on Python‑based analytical scripts, contributing to enhancements where required to support the development and delivery of research‑driven climate and environmental data products and analytical pipelines.

Main responsibilities in the delivery of timely and quality services: • Application and Integration, • Oversee the operational health and reliability of data integration and platform services by monitoring dashboards, system logs, and pipeline alerting mechanisms to ensure service continuity and uptime commitments. • Configure and deploy country‑specific platform instances, including environment configuration, data partitioning, and role‑based access control, in coordination with DevOps and platform teams

• Architecture, Data and AI, • Produce and maintain accurate and up‑to‑date technical documentation, including API specifications, data catalogues, lineage records, deployment checklists, and issue resolution logs to support auditability and knowledge continuity. • Troubleshoot and resolve data pipeline failures, API integration issues, and schema inconsistencies by identifying root causes, implementing corrective actions, and maintaining structured issue logs and escalation pathways.