Interoperability Data Engineer

Interoperability Data Engineer — Europe-based candidates only

Client: Agency of the United Nations (Geneva)

Location: Remote from Europe.

Duration: 6 months freelance consultancy contract, extendable based on performance and budget availability.

Rate: offsite daily rate Max 410 USD all inclusive.

For a UN Agency based in Geneva, DropaCode is currently looking for a senior Data Engineer to join the team on remote. The Consultant will ensure that multi-source datasets are effectively synthesized, processed, and prepared for use by analytics and modelling teams, enabling the generation of robust predictive insights.

You will be responsible for:

• Support subject matter experts in defining and technically validating the data dictionary mapping layer.
• Document architectural decisions and trade-offs regarding interoperability logic.
• Design Content and specification frameworks in accordance with the UN SMART Guidelines as well as AI agent frameworks and orchestration layers.
• Implement the canonical model as a central "source of truth" derived from the UN Digital Adaptation Kit.
• Configure database environments for high-performance relational and network data.
• Ensure support for low-resource and offline data synchronization between pilot sites.
• Design and implement staging layers for ingestion, validation, harmonization, and transformation of heterogeneous surveillance data.
• Develop automated "skill and agent-driven" pull-push mechanisms for DHIS2, SORMAS, EWARS and other external datasets.
• Implement logic for automated data cleaning, deduplication, and harmonization of heterogeneous data for analytical use.
• Ensure the pipeline handles varied data structures and provides high-fidelity inputs for modeling teams.
• Set up automated schedules for weekly and monthly surveillance reports and sitreps.

• Develop APIs and export tools for "clean data exports" specifically optimized for downstream modeling and threshold analysis.
• Support technical requirements for dashboards and visualizations.

For this role you will need to have experience in:

• Bachelor's degree in Computer Science, Data Engineering, Software Engineering, or a related technical field is required, along with relevant certifications such as HL7 FHIR Proficiency, OpenHIE, and platform-specific credentials for systems like DHIS2 and SORMAS.
• At least 8 years of relevant experience across software architecture and data engineering.
• At least 4 years specifically in public health information systems.
• Experience managing cloud-based and on-premise data platforms
• Proven ability to design and implement interoperability middleware and connectors (e.g., DHIS2, SORMAS, OpenMRS)
• Experience harmonizing surveillance data for advanced analytics.
• Demonstrated experience designing canonical data models and interoperability architectures.
• Experience supporting deployment and scaling of interoperable digital health solutions at country level.
• Experience leading engineering teams and documenting architectural decisions.
• Strong track record of collaborating with epidemiologists, surveillance officers, emergency response teams, and cross-functional stakeholders to translate operational needs into reliable, scalable systems.
• Advanced proficiency in Python and SQL for building ETL/ELT pipelines and working with relational databases
• Experience implementing canonical data models and "Data Dictionary" layers for metadata harmonization
• Demonstrated capability in designing interoperability middleware, semantic harmonization layers, and translation engines
• Experience with event-driven architecture, API gateways, modular connectors, and workflow orchestration
• Familiarity with AI/LLM-assisted approaches for data cleaning, entity resolution, and mapping
• Experience building systems for low-resource/offline se