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PepsiCo operates in an environment undergoing immense and rapid change. Big-data and digital technologies are driving business transformation that is unlocking new capabilities and business innovations in areas like eCommerce, mobile experiences and IoT. The key to winning in these areas is being able to leverage enterprise data foundations built on PepsiCos global business scale to enable business insights, advanced analytics and new product development. PepsiCos Data and AI team is tasked with the responsibility of developing quality data collection processes, maintaining the integrity of our data foundations and enabling business leaders and data scientists across the company to have rapid access to the data they need for decision-making and innovation.

What Data Engineers in PepsiCo Data and AI team do:

• Maintain a predictable, transparent, global operating rhythm that ensures always-on access to high-quality data for stakeholders across the company
• Responsible for day-to-day data extraction, load and transformation of PepsiCos corporate data assets
• Work cross-functionally across the enterprise to centralize data and standardize it for use by business, data science or other stakeholders
• Increase awareness about available data and democratize access to it across the company

• Analyze the business / Technical information and map the IT solutions as per the business teams vision
• Performs solution prototyping and Evaluation for new initiatives to define the plan to scale implementations across multiple technology domains.
• Optimize data infrastructure and solutions for performance, scalability, and cost-efficiency, ensuring high availability and reliability.
• Collaborate with cross-functional teams and business teams to understand business requirements and translate them into technical designs and solutions.
• Implement security and compliance measures to protect sensitive data and ensure data privacy.
• Stay up to date with the latest Azure data technologies, tools, and best practices, and provide recommendations for improvement and innovation.
• Leverage team-building skills to collaborate, work, and motivate teams with diverse skills and experience to achieve goals.

• 11 years of experience in developing and maintaining data solutions/pipelines in the Azure ecosystem, including Azure Data Lake, Azure Data Factory, Azure SQL Data Warehouse, Azure Databricks, and/or Azure Synapse Analytics.
• Solid understanding of data engineering principles, data modeling, data warehousing, and ETL/ELT processes which include data testing, validation, and reconciliation processes.
• Working knowledge of cloud service services: IaaS, PaaS, and other Ecosystem services.
• Hands-on experience with data integration and data transformation frameworks, tools, and methodologies.
• Knowledge of data governance, data security, and data privacy practices.
• Experience with cloud-based data storage technologies, such as Azure Blob Storage and Azure Cosmos DB.
• Familiarity with Agile development methodologies and DevOps practices.
• Excellent problem-solving and analytical skills, with the ability to troubleshoot and resolve data-related issues.
• Strong communication and collaboration skills, with the ability to effectively work in cross-functional teams.
• Experience with version control systems, CI/CD pipelines, and automated testing frameworks.
• Knowledge of Cloud data services, Cloud security, and cloud tools.

Good to have:

• Certified in Azure.
• Azure Platform and Networking knowledge.
• Knowledge of streaming technologies, pipelines, and frameworks like Kafka, EventHub, and Azure Stream Analytics.