MISSION M-KOPA’s mission is to make high quality energy affordable to everyone. OUR GROWTH SO FAR… M-KOPA has connected more than 400,000 homes in Kenya,Tanzania and Uganda to solar power with over 550 new homes being added every day. Each 8W battery powered-system comes with three lights, mobile phone-charging and a solar powered radio. Customers can now opt for a 20W system with digital TV. As of July 2016, M-KOPA has connected over 400,000 homes to affordable solar power. Current customers will make projected savings of US$ 300 Million over the next four years.
Description
The analytics engineer will multiply the effectiveness of everyone in the Data and BI team by creating, sharing, and making easy the data systems that workflows are built on, whilst contributing positively to team culture. Our vision is to be the smartest company in Africa and you will play a crucial part in that.
Analytic engineering at M-KOPA is new and evolving, sitting at the intersection of Data Science, BI/Analytics, and Data Engineering. You’ll sit inside a small team with autonomy to improve the data teams workflows. Analytics engineering is a relatively new field, so we welcome applicants from Data Analysts who tend towards repeatability and automation to Data Engineers who are interested in the business domain, data scientists who’ve realized that clean data is more important than another 1000 epochs, or software engineers who want the perfect entry into the data space.
Location: Kenya, UK, Or Remote Working
Responsibilities
- Ultimately the responsibility is to increase the speed and efficiency of common data team workflows. Below are some examples of how you may achieve this
- Improve the overall Data team’s workflow through knowledge sharing, proper documentation, and code review
- Deliver/review new automation frameworks within the team
- Work on efficient ingestion of new data into our data warehouse using tools such as Python, Spark, Airflow, ADF, Databricks, Azure Data Lake, etc
- Work on efficient storage of our data in the data warehouse, identifying performance improvements from query to table redesign.
- Work on the careful design of the schema’s, table names, data models, and practices within the data warehouse, creating a well-curated data set.
- Rewrite our data model using dbt or similar, and empower other analysts to use the frameworks, developing their skills with mentoring and good code review.
- Identify re-usable elements of downstream analytics and move into the repeatable data model
- Contribute to our internal python and R libraries, driving best practice
Experience And Skills
Experience: 3+ years of data experience;
Knowledge / Skills Required
- You are a structured thinker, able to implement structure to simplify workflows and enable teams
- You are curious, from new tools in the data world to what is the right business definition for this metric
- Strong SQL Skills and transforming data
- Experience with collaborative data and software development via git and you’re comfortable in the command line
- Experience deploying code/models to production, ideally via automated deployments
- Experience with Data Warehouse Schema Design
Additional assets
- Experience with python, pandas, airflow
- Experience with dbt (and Jinja) or a similar tool
- Experience with using automated deployment pipelines
- Experience with distributed computing tools such as Spark
- Experience with Microsoft Azure (U-SQL, Data Factory, Data Lake), other Big Data tools (Hadoop, Spark), similar cloud providers and tools also a plus
- Familiarity with agile data ops development processes, unit testing, source control, continuous integration, etc.
- Experience with data visualization tools (such as Power BI or Tableau, GGPlot2, D3.js, Seaborn, Matplotlib, Dash, etc.)
COMPENSATION:
Competitive package covering a monthly salary, performance bonus and medical benefits reflective of the candidate’s experience and skills.
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