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Data & Digital Engineer

Daystar Power Group verified
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Location
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Work Model
home_work onsite
Job Type
work Full-time
Salary
payments Undisclosed

Intelligence Match

Match: ??%

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Skills Match 87%
Experience Match 88%
Portfolio Match 84%
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About the role

Daystar Power Group is a Pan-African provider of solar and hybrid power solutions, offering its systems on a Power Purchase Agreement (PPA), fixed monthly fee lease or buy-out basis. All our solutions are accompanied by comprehensive maintenance services, to ensure the solutions run 365 days a year. We are currently operational in Nigeria, Ghana, Togo, Senegal & Ivory Coast. We are looking to engage a competent and experienced Data & Digital Engineer who will be responsible for unlocking value for the business through data and new technologies especially AI & Hyper-automation. He/she would identify, mature and deliver opportunities through the value funnel that demonstrate benefits. The individual would translate business strategy into data-specific actions and interventions, assess the benefits of new technologies and trends and collaborate with Data Value Owners to deliver key business benefits realization goals. 

Required Skills

SQL AWS Python Machine Learning Microservices Microsoft Azure Power BI

Preferred Skills

Responsibilities

  • Data Modelling and Design: Develop and maintain comprehensive data models that accurately represent data structures and relationships. Design output tables to be provided to customers, identifying data sources/inputs, and suggesting changes. Draft data orchestration to indicate the type of data transformation required at each stage of the flow and scenarios for triggering these transformations. Utilize advanced modelling techniques and tools to create detailed visual representations, including entity-relationship diagrams, dimensional models and data flows
  • Project Delivery: Lead the design and implementation of data models and flows and new Technologies like AI and Hyper-automation in Daystar. Collaborate closely with business analysts, data engineers, and other stakeholders to ensure data models align with business needs and project objectives. Run the initial analysis of the requirement implementation feasibility by presenting the draft of data flow and collecting time and effort estimation from engineers
  • Data Platforms and Technology: Demonstrate an awareness level of understanding of data platforms and strategic technology landscape. Utilize AWS and Power BI for data acquisition, transformation, and visualization. Implement best practices for data management, governance, and compliance
  • Business Collaboration: Engage with business colleagues and end-users to understand their data and KPI requirements. Translate business needs into technical solutions, providing expert recommendations and insights to optimize data usage and reporting
  • Data Assurance: Develop and implement processes for data assurance to ensure the highest levels of data quality and integrity
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