Coca-Cola is the most popular and biggest-selling soft drink in history. An icon of all times, Coca-Cola is the best-known product in the world. Created in Atlanta, Georgia, by Dr. John S. Pemberton, Coca-Cola was first offered as a fountain beverage by mixing Coca-Cola syrup with carbonated water. Coca-Cola was introduced in 1886, patented in 1887, registered as a trademark in 1893 and by 1895 it was being sold in every state and territory in the United States. In 1899, The Coca-Cola Company began franchised bottling operations in and outside the United States taking Coca-Cola to consumers in other parts of North America and Europe and in subsequent years to other parts of the world. In 1951, the refreshing wave of Coca-Cola arrived in Nigeria and has remained a hit with consumers across the country. Packages Coca-Cola is available in: 35cl and 50cl classic glass contour bottle; 33cl on-the-go Can, 50cl and 1.5L PET bottle. Ingredients Carbonated water, sugar, Carbon-dioxide, caffeine, Phosphoric acid, caramel color and flavouring.
About Your New Job
- As DQ Analyst lead with data governance and data quality focuses in the Data, Insights & Analytics (DIA) team, you will be responsible for implementing and executing Intelligent based data solutions to empower the business-led data governance initiatives to hold tight on the quality by working with X-function with good stakeholder relationships, also with the End to End view and understanding of modern data IT landscape and bring more innovation on top of them.
- And manage a professional data team (data analyst and data scientist) as an inspirational leader to keep the team motivated and continue to deliver innovative solutions for fast data quality detection and remediation.
- You will need to “Know the data on both sizes (business and technical)”: understand the business requirements of data quality and translate them to technical solutions; “Do the handson”: implement the data quality detection and remediation through automation and modern data techniques with the best practices of solution building; “Make friends with stakeholders”: build and maintain strong relationships with a diverse group of stakeholders, and “Live in agile with innovation DNA”: understand the iterative nature of data projects and welcome/embrace the changes to ensure high satisfaction for our downstream data users.
- This work will require collaboration with multiple stakeholders and data users, including data curator, data engineers, data scientists, functional teams & functional data owners/data stewards, and other Data & Analytics leads part of DIA team.
Your New Key Responsibilities
In this critical role, you will work with our functional data owners and data stewards to ensure the quality of data for all of our data users, comprising of the following responsibilities:
Hands-on delivery:
- Apply suitable data wrangling techniques to solve the data problems, support ideations, and early stage data understanding with quality and efficiency You don’t ask a friend to do the scripting of a data query for you
- Contribute to improvement of our current Data quality tools and solutions We are building solutions to check the quality of other’s works, so the quality and intelligence level of our works must be “sky high” with best practices of sulution building
- Lead as an example of Data Best practices and continue exploring opportunities for improvements and new learnings No one living in a perfect world, but do you dare to challenge yourself and others to make things better, plus again we are building solutions to check the quality of other’s works, so the quality and intelligence level of our works must be “sky high.”
- Analysis and Translation with deep business understanding and stakeholder relationship:
- Understand the purpose and usage of the data of specific use cases with solid Explorative Data Analytics skills Data is not just numbers, it has many meanings. So you should read and talk about data like you are reading and talking about your favorite books
- Translate the business requirement from idea generation to realization and implementation with the strong Know-how of both sides of the data (Business and Technical) Data is not just numbers, it is like languages, business talks data in the business way, tech talks data in the technical way, you must be bilingual
- Deliver and sustain the data quality End-to-End solutions alongside the Data owners all our data users together with data owners as their representative stakeholders, are you customer, talking about user centricity, you will be their best friends
People leadership:
- This role requires to lead and manage a team of top notch smart data analyst and data scientists You will need to win their hearts by “show your magic” and motivate them to "fly even higher"
- Empowering the team by helping them to remove obstacles and lead the problem solving is the wining formular Just delegating won’t lead you to the success
Are These Your Secret Ingredients?
- Master's Degree preferred or Degree Emphasis in Computer Science, Engineering, or Data related subjects with 10 years of Data Analytics experience required
- 4+ years of experience managing technical data team
- Proven track record of understanding business challenges and translating them into valueadd and technically capable end solutions
- A strong working knowledge and experiences in data management
- Data wrangling and engineering skills: from simple Excel vlookup to advanced ETL e.g. Python, SQL, PySpark, plus not need to mention understand data model and do data modeling by yourself
- Data platform: SQL DB, Data Warehouse, Datalake, Databricks
- Data Visualization: from simple Excel Histogram to Python Matplotlib to PowerBI (Nice to have)
- Understand Agile Product Delivery (SAFE framework is preferred)
- Previous experience working with CPG sector and its core datasets is a big plus
- Knowledge and experience working with data science or AI projects is a bigger plus.
Method of Application
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