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M-Kopa – Senior Analytics Engineer.

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About M-KOPA

At M-KOPA, our aim is to increase access to life-improving technologies at huge scale. We do this through an innovative credit model – pay-as-you-go asset financing – of which M-KOPA was an early global pioneer. With offices in Nairobi, Kampala, Lagos, and London, M-KOPA serves over 1 million low-income households in Sub-Saharan Africa. Since its commercial launch in 2012, M-KOPA has made its name in off-grid solar power, providing customers with solar panels and solar-powered lights, televisions, radios, fridges, and more – this is often our customers’ first access to electricity.

M-KOPA’s affordable credit model can also be applied to assets beyond off-grid solar power, and in 2019, we began providing credit for smartphones, which enables our customers to move from feature phones to smartphones and improve their connectivity, communication, and information access. Today, smartphone financing is a rapidly growing business line – with enormous opportunities for innovation and increasing our customer impact. 

M-KOPA currently employs over 1,000 full-time staff across its operating countries. We value progress, innovation, pragmatism, collaboration, and – most of all – our customers. We have been well recognised for our pioneering business model and scale.

Job description

M-KOPA is looking to welcome a Senior Analytics Engineer to join our Analytics Engineering team. You will multiply the effectiveness of everyone in the data science, bi and engineering teams by creating and maintaining the data infrastructure and systems that our analytics workflows are built from. Our vision is to be the smartest company in Africa and you will play a crucial part in that. 

With over a million customers across multiple geographies, our data is essential to both everyday operations and business decisions. Analytic engineering at M-KOPA is new and evolving, sitting at the intersection of Data Science and Analytics, Reporting and Data Engineering. Your contributions will be key to ensuring our data science and analytics activities can scale with the rich, high volume datasets generated by the M-KOPA ecosystem. We are looking for someone who is familiar with and understands the requirements of analytic workstreams while bringing engineering best practices and rigor to build robust systems and processes.  

Specific responsibilities

Ultimately the responsibility of the Analytics Engineer is to be an Enabler; to build systems and processes that provide reliable and easy access to our data and enable the wider data team to work more efficiently.

Below are some examples of how this can be achieved:

  • Increase the velocity of our transition to a modern data stack (dbt, Airflow, Python, Spark, Synapse, Kubernetes, Docker, + ….)
  • Design and collaborate on efficient data ingestion to our data warehouse from data sources including published events, data lakes, data bases and API integrations.
  • Develop automation frameworks for data pipelines and analytics processes.
  • Set high standards of work including security, infra as code, documentation etc 
  • Integrate and maintain the infrastructure used in data analytics workstream (data lakes, data warehouses, automation frameworks)
  • Contribute to the design and implementation of a clear, concise data model.
  • Contribute to efficient storage of our data in the data warehouse, identifying performance improvements from table and query redesign.
  • Write quality ELT code with an eye towards performance and maintainability and empower other analysts to use and contribute to ELT frameworks and tools.
  • Improve the overall Data team’s workflow through knowledge sharing, proper documentation, and code review.
  • Abstract logic into libraries and patterns of work that enable teams to build value from our data independently.

 Experience and skills

Required

  • You enjoy abstracting, generalizing, and creating efficient, scalable solutions where they are needed.
  • You enjoy creating patterns and processes as well as solving presented problems.
  • Strong foundation of software development best practices (collaborative development via git, testing, continuous integration, deployment pipelines and infrastructure as code).
  • Strong SQL Skills.
  • Experience with python.
  • Experience deploying code to production via automated deployments on the cloud.
  • Experience working on associated platforms (Azure, AWS etc).

Additional assets

  • Experience building ingestion and/or reporting from streaming datasets and event architectures.
  • Experience with distributed compute tools such as Spark and DataBricks.
  • Experience with dbt or a good basis to learn it from.
  • Experience with orchestration tools such as Airflow.
  • Familiarity with using analytics or working with analytics teams.
  • Experience with Kubernetes not expected but a plus.
  • Experience with data visualization tools such as PowerBI, Looker or Tableau not expected but a plus

M-KOPA Solar is an equal opportunity and affirmative action employer committed to assembling a diverse, broadly trained staff. Women, minorities and people with disabilities are strongly encouraged to apply. In compliance with applicable laws and in furtherance of its commitment to fostering an environment that welcomes and embraces diversity, M-KOPA does not discriminate on the basis of race, colour, creed, religion, national origin, sex (including pregnancy and parenting status), disability, age, sexual orientation, gender identity or expression, marital status or genetic information in its programs or activities, including employment.

M-KOPA, as a policy, does not collect/charge any money as a pre-employment or post-employment requirement. This means that we never ask for ‘recruitment fees’, ‘processing fees’, ‘interview fees’ or any other kind of money in exchange for offer letters or interviews at any time during the hiring process.

M-KOPA reserves the right to close or extend this job advertisement depending on the number of candidates received.

Degree qualifications

  • Bachelor’s Degree

Skills

 



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