Analytics Engineer Team Leader
hace 3 semanas
**Are you looking for an opportunity to work in a company where progress and humility are valued as highly as technical excellence? At M-KOPA we use the latest technologies and architectures to build fantastic customer experiences with a socially and environmentally conscious mission that echoes throughout the organization.**
- We are looking for a Senior Analytics Engineer with that managerial experience to join our Analytics department. This is a Senior Team Leading role reporting directly to the Head of Analytics._
**Team Focused**:
Leading a small 3 or 4 person team role focused on Dimensional Data modelling, Data Engineering, Business and Product Optimization, Cloud Platform Utilization and Data Management.
Tools could include, SQL, Python, Power BI, Looker, Tableau, dbt, and airflow, all Cloud based.
Your team will collaborate primarily with cross-functional product teams with some additional internal business units to gather requirements, understand business needs, and deliver data-driven recommendations.
Often simplifying very complex and unstructured data into answers, testing hypotheses and delivering insights. This is a low ego creative environment where careers can thrive.
**Background**:
If you have a background working in FinTech B2C environments where big data is leveraged for products and projects and you are comfortable building and managing large data sets then this might be the right place for you.
Alternatively a background in consumer based high volume environments like, Travel, eCommerce, Delivery or Mobility could be useful.
**Work - Life Balance**:
This is a remote role in a team that spans from the UK, through Europe to Africa. Work in a similar distributed environment would be ideal.
At M-KOPA, we empower our people to own their careers through diverse development programs, coaching partnerships, and on-the-job training. We support individual journeys with family-friendly policies, prioritize well-being, and embrace flexibility.
We are proud to have been recognised twice by the Financial Times as one Africa's fastest growing company (2022 and 2023) and by TIME100 Most influential companies in the world 2023, we've served over 3 million customers, unlocking $1 billion in cumulative credit for the unbanked across Africa.
If the above is of interest to you, please apply.
**Optional Application Task**
**Question 1**
Imagine the following query being issued against a distributed analytics engine, such as Google Big Query or Redshift.
SELECT sale_date, SUM(TotalAmount) / COUNT(DISTINCT salesperson_id) AS SalesPerPerson FROM sales GROUP BY sale_date
[sales] table has one row for each product item sale transaction.
What part of the query would cause the most data movement between the compute nodes?
How would you optimize the query or data model to answer the same question with less data movement between compute nodes without loss of precision?
**Question 2**
Given the following Entity Relationship diagram describing a generic Shop selling products, please write a SQL query that answers the following question:
“Which two Shops have the highest and the lowest productivity respectively in the last 28 days?”
Shop productivity is measured by monetary value of sales divided by total salesperson work-hours in the same time period.
M-KOPA 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.
M-KOPA explicitly prohibits the use of Forced or Child Labour and respects the rights of its employees to agree to terms and conditions of employment voluntarily, without coercion, and freely terminate their employment on appropriate notice. M-KOPA shall ensure that its Employees are of legal working age and shall comply with local laws for youth employment or student work, such as internships or apprenticeships.
M-KOPA 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.
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