Senior Analytics Engineer at M-KOPA

Category: Technology - Analytics

Job Summary
Team Mission:

• The Analytic Engineering team's mission is to increase the value people at M-KOPA get from our data.

Vision:

• We recognise that data is a critical asset when consumed by humans and we want to deliver better tools and best practices to enable M-KOPA's humans to deliver value.
• We are a highly leveraged team in that the best use of our time is to increase the value everyone can deliver with data or get from data in the limited time they have.

Vision Statements:

• Analysts and Data Scientists are increasingly taking advantage of engineering best practices such as testing, CI, automated deployment etc.
• Analysts and Data Scientists are empowered to release data pipelines and novel transformations
• Engineers and product managers are increasingly able to answer data questions, with what qualifies as a ticket becoming increasingly interesting over time.
• Data is robustly tested and well trusted.

Job Description

• We serves over a million customers across multiple (African) geographies and is growing fast. From lights to phones and e-bikes we are powering progress through internet connected devices.
• You will own analytics models for a specific technology domain. You’ll deliver high performance explorable datasets that enable your teams to serve the metrics that they and the stakeholders care about. 
• This work will range from standard BI models - how many devices did we sell, through to product analytics - how can we use metrics to understand and improve the sale process. 
• Throughout this process you will apply Analytics Engineering best practice to build reliable, well tested, efficient, documented data models in dbt and Looker to enable self serve analytics in your domain.
• This role is Remote within the following time zone (UTC -1 / UTC+3) - this role will report too Head of Engineering Analytics.
• We're looking for a Senior Analytics Engineer to join the team and:
• Be a technical leader on data modelling in dbt and Looker
• Own a specific domain teams (or a group of teams) analytics models
• Demonstrate best practices across the data stack, and optimize the highest leverage opportunities to improve data processes, whether at data load, or with data model redesign.
• The stack is managed by the analytics platform team who you’ll work closely with.  

Requirements
You will have most of the below:

• 5+ years experience working with relational data models
• 2+ years working with dbt
• 3+ years with BI tools like Looker
• 2+ years working with a scheduling tool like Airflow
• 3+ years working with modern data warehouses (and appropriate knowledge on efficient querying on them)
• A clean tidy and structured approach to work and code
• Demonstrable comfort with software best practices (version control/git, agile, testing, automated release pipelines, logging, observability etc.)
• Ideally familiar with an event based architecture.

Current stack:

• Dbt for Transformation
• Looker for visualisation
• Spark + Data Factory + Event Hub + Airflow for ingestion (we’re working on making this simpler in platform)
• Airflow + AKS for orchestration
• Microsoft Azure as our base cloud provider