Expert Data Harmonization

Heritage Alliance Ltd is a health research and data science company based in Belgium, working with partners in Africa and internationally.

Who we are

We connect clinical knowledge with data engineering so that partner institutions can produce interpretable, traceable datasets for research and health-system improvement.

Health Data Sciences & Advanced Analytics: Data profiling, terminology alignment and validated analytical datasets that support comparable analyses across institutions.

Complex Clinical Research, including Clinical Trials and Implementation Science: Harmonisation of clinical, registry and study data, with transparent definitions, provenance and documented limits on secondary use.

Innovation & Digital Health Systems Development: Maintainable interoperability pipelines and local data capabilities that support national and federated health-data networks.

A mission-driven environment: Improve the usefulness of routinely collected health data for locally relevant research.

Cutting-edge technologies: Work directly with OMOP CDM, OHDSI tools and containerised data infrastructure.

International exposure: Collaborate with data owners, clinicians and technical teams across partner countries.

Growth and leadership opportunities: Shape mapping standards, review implementations and mentor site-based data engineers.

We seek an engineer who can follow a clinical fact from its original record to its analytical representation, explain every transformation and demonstrate that the resulting data are fit for their intended use.

You will work with source-system owners, clinicians and analysts to deliver documented, repeatable harmonisation pipelines. You will also support local teams in operating and improving those pipelines after deployment.

• Assess source data: Profile OpenMRS and other electronic medical record (EMR) databases, registries, laboratory systems and authorised extracts; document schemas, clinical workflows, coding practices, coverage and quality limitations.
• Design mappings: Specify source-to-target mappings for OMOP tables, fields, relationships and observation periods; retain source values and document assumptions, exclusions and information loss.
• Manage clinical terminology: Map local codes through the OHDSI Standardized Vocabularies, using Athena and Usagi where appropriate; distinguish source codes from valid standard concepts and obtain clinical review of ambiguous mappings.
• Build ETL pipelines: Implement extract, transform and load (ETL) workflows in SQL and Python or R, including repeatable full and incremental loads, dependency management, error handling and reconciliation.
• Handle clinical detail accurately: Reconcile identifiers, encounters, diagnoses, medicines, laboratory values, units and dates; preserve longitudinal relationships and record lineage without altering source clinical records.
• Validate the outputs: Use the OHDSI Data Quality Dashboard and Achilles, alongside source-to-target counts, distribution checks and clinical review; investigate failures and document fitness for specific analyses.
• Operate the OHDSI environment: Deploy and troubleshoot OHDSI Broadsea and relevant services such as ATLAS and WebAPI using Docker Compose; work with infrastructure colleagues on access controls and production configuration.
• Maintain versions and interoperability: Track CDM, vocabulary and mapping versions; assess change impacts; support interfaces using Health Level Seven (HL7) Fast Healthcare Interoperability Resources (FHIR) where required, with explicit transformation specifications.
• Enable sustainable use: Deliver mapping specifications, automated checks, release notes and operating instructions; prepare local datasets for authorised federated analyses and train partner data engineers.

Travel and on-site work: Partner-site assessments, deployment support and practical training, according to project needs.

Essential

• A degree in computer science, data engineering, health informatics, biomedical informatics or a related field, or equivalent substantial professional experience.
• Demonstrated delivery of an end-to-end health-data harmonisation pipeline into OMOP CDM, including terminology mapping, validation and subsequent maintenance.
• Strong SQL skills and practical programming in Python or R; experience with relational databases, Git and repeatable data-processing workflows.
• Hands-on experience extracting and interpreting data from OpenMRS, another EMR or a comparable longitudinal clinical registry; ability to navigate patient, encounter and observation relationships.
• Practical knowledge of OMOP domains, concept relationships and the OHDSI toolchain, including Athena, Usagi, Data Quality Dashboard, Achilles, ATLAS and WebAPI.
• Experience deploying or troubleshooting Broadsea with Docker Compose, and confidence working in Linux-based environments.
• Working knowledge of clinical terminologies and classifications such as SNOMED CT, LOINC, ICD and RxNorm, including local coding limitations and relevant licensing conditions.
• Clear documentation, careful handling of sensitive data, fluency in English and a good command of French.

Desirable

• Experience with OpenClinic GA, laboratory information systems, disease registries, DHIS2, HL7 FHIR or national interoperability architectures.
• Experience with workflow orchestration, database performance tuning, federated research networks, African health systems or training data engineers.

Remuneration: Negotiable, reflecting experience, responsibilities, duty station and contract arrangements.

Career development: Professional development in OHDSI methods, terminology engineering and health-data architecture, with opportunities to lead harmonisation workstreams.

Working environment: Multidisciplinary collaboration, access to relevant technical resources and opportunities to contribute to international health research. Benefits and working arrangements will be specified in the employment offer.

Women are encouraged to apply.