Data Engineer Job at S4D Consulting LLC

  • Published date: January 18, 2022
  • Category: Engineering
    • Location: Nairobi, Nairobi
  • Jop type:
  • Salary: Ksh Not mentioned
  • Company name: Jobs in Kenya

Job Description





Job Summary


The Data Engineer will be responsible for finding trends in data sets and developing algorithms to help make raw data more useful to the MoH /GHS enterprise. S/He will be responsible for constructing datasets that are easy to analyze and support the MoH /GHS requirements and building and maintaining the entire data ecosystem.



  • Minimum Qualification: Masters

  • Experience Level: Senior level

  • Experience Length: 5 years










Job Description/Requirements



S4D Consulting LLC.


JOB DESCRIPTION


 


 


TITLE:   Data Engineer


PROJECT: Global Fund to Fight AIDS, Tuberculosis and Malaria (the “Global Fund”) Data Production and Use Project


 


1. Background


The Service Delivery Innovation Strategic Initiative was approved by the Global Fund Board to support the achievement of the Global Fund’s 2017-2022 Strategy to build Resilient and Sustainable Systems for Health (RSSH). Its aim is to support innovations that strengthen health service delivery and improve HIV, TB, and malaria outcomes. Under this objective, the Global Fund is providing support to the Government of Ghana (GoG) to increase the use of data to manage its supply chain operations for improved efficiency and increased impact.  This will be done through facilitating the implementation of MoH and GHS data management framework that will ensure implementation of quality data production mechanisms and establishment of a culture of data use in all supply chain management decision making and performance management.  


 


2. Data Engineer


As part of developing the data structure, ensure quality data production and restructure the culture of data use in MoH and GHS to take advantage of new scalable technology to provide quality data to support and facilitate informed decision making, S4D will establish a data management framework, oversee its implementation, and ensure capacity is built to sustain its usage in Ghana public health supply chain management and decision making.  The Data Engineer will be responsible for finding trends in data sets and developing algorithms to help make raw data more useful to the MoH /GHS enterprise. S/He will be responsible for constructing datasets that are easy to analyze and support the MoH /GHS requirements.


S/He will be responsible for building and maintaining the entire data ecosystem of the MoH/GHS, which includes everything from data sources and databases to data storage solutions.  S/He will also be responsible for building data pipelines that are used to transport data from all data sources to a data warehouse while implementing methods to improve data reliability and quality. These pipelines are crucial: they are what will enable the MoH/ GHS access and analyze its data and use the insights to make business decisions. S/He will also develop and test architectures that enable data extraction and transformation for predictive or prescriptive modeling.  S/He will develop models to categorize unstructured data. This process gives rise to structured data: objective facts and numbers that most analytics software can collect and interpret. The data engineer will also handle the design and construction of scalable management systems and ensure that all data systems meet the enterprise’s requirements.


 


3. Job Description


•    To ensure effective data production and use, the data engineer will take leadership in performing the following activities:
•    Develop models that will analyze and organize raw data.
•    Build data pipelines that will enable the MOH/GHS collect data points from users and process the results in near real-time
•    Build algorithms and pipelines that make it easier for users in the MoH/GHS enterprise access raw data while understanding business requirements and where data fits into the business model in order to meet the enterprise’s needs.
•    Prepare data for prescriptive and predictive modelling
•    Design, construct, install, test and maintain data management systems.
•    Integrate up-and-coming data management and software engineering technologies into existing data structures.
•    Employ an array of technological languages and tools to connect systems together.
•    Collaborate with members of the team on the project's goals.
•    Recommend different ways to constantly improve data reliability and quality.
•    Explore ways to enhance data quality and reliability
•    Identify opportunities for data acquisition


4. Desired Key Skills



  • Ability to build and optimize data sets, ‘big data’ data pipelines and architectures 

  • Ability to perform root cause analysis on external and internal processes and data to identify opportunities for improvement.

  • Excellent analytic skills associated with working on unstructured datasets 

  • Ability to build processes that support data transformation, workload management, data structures, dependency, and metadata


5. Qualification


1.     Masters’ degree (preferred in Computer Science, Statistics, or any quantitative field).


Have a solid understanding of relational databases, and the applications and programs used by those databases.


2.     Understands data modeling, including conceptualization and database optimization


3.     Minimum 5 years of professional experience, preferably in consulting or at high-tech companies


4.     Strong passion for the following topics – Machine Learning, Data Quality Management, Data warehousing


5.     Understanding of Supply Chain Control Towers


6.     Strong knowledge of Visibility and Analytics Networks


7.     Ability to develop strategies for data management and data production and use


8.     Practical knowledge of tools, frameworks & technologies within at least one of the following categories:


a.     Business Intelligence (Power BI, Tableau, Qlik)


b.     Machine Learning (R, Python, SAS, SPSS)


c.     Big Data (Spark, Hadoop, NoSQL Databases, Data Lakes & Platforms)


d.     Cloud Platforms (Azure, Google Cloud, AWS)


9.     Strong knowledge of technology trends across IT and digital and how they can be applied to companies to address real world problems and opportunities


10.  Team oriented and collaborative working style, both with clients and those within the organization


11.  Growth mindset, positive attitude & strong interest to solve client challenges, adapt to a changing work environment & deal with new issues


12.  Excellent written and verbal communication skills


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