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Safeguarding – We define Safeguarding as “the preventative action taken by Palladium to protect our people, clients and the communities we work with from harm”. We are committed to ensuring that all children and adults who come into contact with Palladium are treated with respect and are free from abuse. All successful candidates will be subject to an enhanced selection process including safeguarding-focused interviews and a rigorous due diligence process.
Funded under the US President’s Emergency Plan for AIDS Relief (PEPFAR) through a cooperative agreement with the US Centres for Disease Control and Prevention (CDC), Palladium Development and Consultancy Kenya Ltd (Palladium Kenya) anticipates 5-year funding to support the Kenya Ministry of Health, county governments and healthcare service delivery partners to implement technological innovations in health information systems.
These innovations include the scale up of electronic medical records systems (EMRs) for clinical decision support and improved patient care, the enhancement of the Kenya National Data Warehouse (NDWH), a centralized data repository of data from EMRs for analysis and reporting, the development of an interoperability layer to support the exchange of data across systems, the enhancement of mHealth solutions and numerous other innovations including patient identification and informatics solutions to support health surveillance.
Primary Duties and Responsibilities:
- Responsible for developing and maintaining the data infrastructure for analytics and reporting
- Creation of ad-hoc datasets used in modeling, mining, acquisition, and verification.
- Developing data extraction routines for EMR platforms and for data in the data warehouse
- Ensuring formulas and indicator definitions in the DWH are in concordance with the EMR guidelines definitions (PEPFAR & MoH)
- Work closely with the Data Analysis and Use Team in developing information products for the various stakeholder groups.
- Assembling large, complex sets of data that meet non-functional and functional business requirements
- Be part of discussions with product manager and data analyst to guide them in their understanding of the data in the data repository, shape the product solutions and to better grasp the context of requirements coming your way
- Capture business requirements for analytics and translate complex ones into technical requirements. Collaborate with data engineers to design & implement end-to-end solutions
- Use SQL queries to transform data in our data repository to move it from raw nuggets into reliable business entities and then into reporting aggregates. Identify dependencies for these transformations. Schedule these transformations on our platform. Investigate discrepancies in data.
- Document analytics datasets and any business logic
- Lead some refactoring of data warehouse where needed, to make data more consistent, better documented and the pipelines more resource-efficient
- BSc degree in Computer Science/Computer Engineering. Masters is a plus.
- A minimum of 5 years’ experience in the same or similar position.
- Strong competencies in algorithms and software architecture.
- Excellent SQL knowledge with the ability to understand, manage and handle complex data and create efficient data models (applied to data warehousing in particular)
- 3+ years of experience with Data Warehousing, DBT or SSIS or Opensource ETL Tools
- 5+ years of Software engineering experience with hands-on experience automating tasks with scripting.
- Ability to work with multiple parts of the business (product, ads) and multiple stakeholders (engineers, analysts, product managers…)
- Have basic knowledge of machine learning to understand data scientist’s needs better (and, by extension, the organization’s needs), get models into production and build more accurate data pipelines.
- Experience in creating project plans to identify tasks, milestones, and deliverables.
- Proven experience with project management tools (Jira / Microsoft Project) is a plus
- Passionate about data visualization. Experience with any of the mainstream visualization tools such as Power BI, Tableau, Qlik.
- Demonstrated experience modelling data in analytics and the ability to develop data models that cater to specific domains—both conceptual and physical models.
- Strong communication. Ability to articulate complex problems/solutions for the senior stakeholder to understand