Data Platform Engineer - Global

P&G was founded over 180 years ago as a simple soap and candle company. Today, we're the world's largest consumer goods company and home to iconic, trusted brands that make life a little bit easier in small but meaningful ways. We've spanned three centuries thanks to three simple ideas: leadership, innovation and citizenship. The insight, innovation and passion of hardworking teams have helped us grow into a global company that is governed responsibly and ethically, that is open and visible, and that supports good causes and protects the environment. This is a place where you can be proud to work and do something that matters.

Dedication from Us: You'll be at the core of breakthrough innovations, be given exciting assignments, lead initiatives, and take ownership and responsibility, in creative workspaces where new insights thrive. All the while, you'll receive outstanding training to help you become a leader in your field. It is not just about what you'll do, but how you'll feel: encouraged, valued, purposeful, challenged, heard, and inspired.

What we Offer: Continuous mentorship - you will collaborate with peers and receive both formal training as well as day-to-day mentoring from your manager dynamic and encouraging work environment- employees are at the centre, we value every individual and support initiative, promoting agility and work/life balance.

We're looking for a Data Platform Engineer to join our Data & Analytics Platforms RUBIK engineering team and help build modern, scalable data solutions that power global business capabilities. In this role, you will use Agile and DevOps practices to design, develop, and enhance IT systems and applications across multinational teams. This is an exciting opportunity for a self-motivated engineer who enjoys solving complex technical challenges, driving innovation, and delivering high-impact global projects.

Responsibilities:
• Support Data & Analytics applications through the full lifecycle, from development and deployment to upgrades and retirement.
• Write and test infrastructure code and build cloud-native Azure solutions for data and analytics use cases.
• Develop and maintain data pipelines and data engineering workflows to enable reliable, scalable, and efficient data processing.
• Design and implement data ingestion, transformation, and integration processes to support analytics, reporting, and downstream applications.
• Ensure data quality, consistency, and availability by applying validation, monitoring, and operational best practices across data workflows.
• Use Apache Airflow to orchestrate, schedule, and monitor data workflows.
• Ensure solutions follow engineering standards and modern delivery practices such as CI/CD, Agile, DevOps, automation, and testing .
• Collaborate with internal teams and vendors to deliver solutions that improve performance, efficiency, and business capabilities.
• Investigate and resolve technical, integration, and performance issues across applications and data platforms.
• Contribute to platform improvements, documentation, and engineering best practices.

Ideal Candidate:
• Experience in Data Platform Engineering, Data Engineering, or software engineering roles python , with hands-on delivery of cloud-based data solutions.
• Strong knowledge of Azure, data pipelines, ETL/ELT, data integration, and Apache Airflow for building and supporting scalable data workflows.
• Familiarity with modern engineering practices including CI/CD, DevOps, Agile, automation, and infrastructure as code .
• Collaborative, detail-oriented, and proactive, with strong problem-solving skills and the ability to work effectively with cross-functional teams and stakeholders.

Job Qualifications
• Bachelor's degree in Computer Science , a related technical field, or equivalent practical experience.
• At least 5 years of experience working with Azure Cloud in a DevOps, Data Platform Engineering .
• Hands-on experience building and supporting cloud-native Data & Analytics solutions on Azure , including writing and testing code.
• Strong knowledge of Docker, Kubernetes, Helm, Istio, Terraform, and Terraform Cloud .
• Practical experience with DevOps tools and practices, including Azure DevOps CI/CD, GitHub Actions, SonarQube, Grafana, and Prometheus .
• Experience with data pipelines, data integration, and workflow orchestration tools such as Apache Airflow .
• Strong communication skills and a commitment to high-quality engineering practices , including collaboration, testing, and code reviews.