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 Sr. DQ Analyst with data governance and data quality focuses in the Data, Insights & Analytics (DIA) team, you will be responsible for implementing and executing the business-led data governance initiatives to hold tight on the quality of the upstream part of the data value chain, also with the End to End view and understanding.
- 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 hands-on”: implement the data quality detection and remediation through automation and modern data techniques; and “Live in agile”: 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:
Analysis and Translation:
- 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, are you customer, talking about user centricity, you will be their best friends
- Work with a multidisciplinary team (Data Scientist, Insights Expert, Data Engineer, Data Curator, incl. Vendors) with strong problem-solving skills, e.g. Active listening, Research, Creativity, Communication, etc. Yes, as a big organization, our data landscape is enormous with all kind of data roles you can image. If you are thinking “Gobig”, this is your “home”
Hands-on delivery:
- Apply suitable data wrangling techniques to solve the data problems, support ideations, and earlystage data understanding with quality and efficiency You don’t ask a friend to do the scripting of a data query for you
- Implement the data standard and data quality rules, monitor the adoption level and be able to own the tooling and codes for changes and updates - This is not just a “click a button” type of job, you need to know what “behind ofbutton” and own it
- Contribute to the innovation and 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”
- 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”
Are These Your Secret Ingredients?
- Master's Degree preferred or Degree emphasis in Computer Science, Engineering, or Data related subjects with min 4+ years of Data Analytics experience required
- 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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