Informacje o stanowisku

Join our dynamic Grooming Data Hub team in Warsaw as a Senior Data Engineer and be a pivotal force in shaping the future of our iconic Braun and Gillette brands. We are on the lookout for self-motivated professionals who bring a wealth of experience in data ingestion, cleansing, harmonization, and the development of robust data pipelines and transformations across Azure and IT/OT on-premise platforms.

In this influential role, youll empower data-driven decision-making and automation supported by cutting-edge AI technology. This is an extraordinary opportunity to engage in exciting global projects and collaborate with diverse, multi-functional teams both within and beyond P&G, making a meaningful impact on our business.

Key Responsibilities:

Data Maintenance and Management:

• Take charge of maintaining and managing extensive datasets from digital twin simulations and curate libraries of sampled data from production systems.

• Oversee libraries of model versions and validation datasets, ensuring they are up-to-date and accessible.

• Develop and maintain annotation schemas and labeling ontologies in partnership with P&G’s AI Factory.

• Guarantee data integrity, consistency, and availability across IT/OT systems

• Set up and document a Data Version Control (DVC) system to meticulously track datasets, model weights, and configurations; in coordination with GitHub version controls.

Data Modeling and Architecture:

• Enforce data governance policies to uphold data security, privacy, and compliance.

• Collaborate with business stakeholders to deeply understand data requirements, ensuring our data models are aligned with their needs.

Cloud / Hybrid Infrastructure Management:

• Efficiently distribute and store data within P&Gs Microsoft Azure cloud infrastructure.

• Collaborate with IT/OT platform teams to create configurations for Kubernetes, GitHub runner VMs, and model registries.

• Implement best practices for cloud data storage, security, and distribution, ensuring a balanced approach to cost and value.

• Design and build scalable data pipelines using cloud technologies, including advanced ETL (extract, transform, load) processes.

• Collaborate closely with IT and digital infrastructure teams to streamline data access and usage.

Continuous Improvement:

• Stay ahead of the curve by keeping abreast of the latest industry trends and technologies in data engineering and cloud computing.

• Propose and implement innovative solutions that enhance data management, processing, and distribution practices.

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