Data & Analytics Manager

at  CocaCola

The Coca-Cola Company is looking for Manager to analyze, interpret, and document business processes, products, services, and technology. This role will support product teams to design, build, and implement data and analytics products and solutions for various stakeholders and the enhancement and maintenance of products thereafter. Will work with cross functional teams across product, technology, and subject matter experts to deliver projects.
The role will report into the Data Platform & Ops team lead in the Asean South Pacific D&A Team.

QUALIFICATIONS & REQUIREMENTS:

• Bachelor’s degree or equivalent in Computer Science, Software Engineering, Management Information Systems, Data Science, or related field.
• 3+ years of developing and managing data products from ingestion to operations and maintenance.
• 3+ years of experience supporting data analytics solutions, including troubleshooting issues and incidents management.
• Experience using Python and working with relational SQL databases
• Proficient in PowerBI (Desktop, Dataflow, Workspace etc)
• Experience using CI/CD tools – Bitbucket, GitHub, GoCD, Bamboo, Terraform
• Solid understanding of Git-based version control
• Solid knowledge about data modeling and architecture
• Demonstrated proficiency in using Azure platform for Data and Analytics products specially focused in Data Services (CosmosDB, DynamoDB, Databricks, Glue, DataLake, Redshift etc.)
• Experience in Agile\DevOps project methodology.
• Experience in FMCG/ CPG companies or retail/ market data an advantage.

SKILLS:

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The Analyst key responsibilities are:

• Analyze business analytical requirements (e.g., functional and technical requirements, data need, business processes) by conducting information-gathering sessions with clients, analyzing the information and prioritizing the requirements to gain understanding of the business needs.
• Develops data analytics products (new data ingestion, data processing ETL, data enhancements, master data, data integration). Connect business process to data product functionality and ensure the reuse, integration, maintainability and efficiency.
• BI/Analytics solutions that are visually pleasing, easy-to-use and understand, and that drive actionable insights and business value.
• Compliance with industry best practice software and company technical architecture standards
• Maintain good data governance and data quality for analytics solutions.