Consultant – Senior Data Platform Architect NGO Job Living Goods
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Role Summary:
- The Senior Data Platform Architect will work within the Ministry of Health to support the Division of Community Health Services and will lead the design and optimization of scalable, secure, and high-performing data systems that power digital health programs and analytics. This role is responsible for building robust data architecture that enables reliable data exchange across health information systems, supports advanced analytics and AI, and ensures the highest standards of data quality, security, and compliance. The position works at the intersection of technology, public health, and data science to enable data-driven decision-making and improved health outcomes at scale.
Key Responsibilities:
Data Architecture Development
- Design and implement scalable database structures, data warehouses, and data lakes to support large volumes of structured and unstructured healthcare data.
- Define data models, standards, and architecture patterns that enable interoperability across digital health platforms and national health information systems.
- Establish cloud and hybrid data infrastructure aligned with performance, scalability, and resilience requirements.
Data Engineering
- Develop and maintain robust ETL workflows to facilitate seamless data movement between different health information systems.
- Implement automated data ingestion, transformation, and synchronization processes to support near real-time data availability where required.
- Implement data validation techniques to ensure the accuracy, consistency, and reliability of health records and analytics.
- Ensure compliance with health data protection laws and enforce stringent security measures to safeguard patient data.
- Support the implementation of data governance practices, including metadata management, data standards, and auditability.
Performance Optimization
- Support risk management and disaster recovery planning for critical data systems.
- Continuously optimize data storage, indexing, and retrieval strategies to improve query performance and system efficiency.
- Reduce redundancy and improve resource utilization across the data environment.
- Work closely with software engineers, data scientists, and public health officials to create data-driven insights for healthcare interventions.
- Continuously refine data storage and retrieval methods to improve query speed, reduce redundancy, and enhance overall system efficiency.
- Assist in the implementation of AI/ML models for predictive analytics, helping to improve health outcomes through intelligent data analysis.
Government engagement & program management
- Provide day-to-day coordination for set deliverables in data workstreams, communications, stakeholder updates and government-led milestones including definition of data dictionaries.
- Train and coach country digital leads, program managers, M&E staff and supervisors on best practices and governance for data design, platforms, security and governance.
- Ensure compliance with Government regulations and policies, the deliverables of the program and contractual requirements.
- Support teams to translate data operational models for government adoption by helping cost, plan and prepare for national scale.
- Co-design data workshops, capacity-strengthening curricula and technical assistance packages for government and implementation partners.
- Work in close collaboration with the CHU4UHC Secretariat to strengthen coordination and performance visibility across coalition members. This includes providing structured support to track, analyse, and report on coalition performance against agreed high-level indicators.
Required Qualifications & Experience:
- Ability to communicate with clarity and work effectively with diverse team members.
- Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field.
- Proficiency in SQL, NoSQL databases, and big data processing frameworks such as Apache Spark or Hadoop.
- Experience with cloud-based data storage solutions (AWS Redshift, Google BigQuery, or Azure Synapse Analytics).
- Knowledge of data standards such as FHIR and HL7, and experience working with electronic medical records (EMRs) or health management systems.
- Familiarity with Python, R, or Scala for data manipulation and analysis.
- Strong analytical skills and the ability to develop data-driven solutions to health-related challenges.
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