Data Engineer

Efficient Data Pipeline Implementation

• Design and implement efficient data pipelines that integrate information from various sources and business domains. The goal is to develop globally harmonized data models and perform KPI calculations, ensuring consistency and accuracy across the organization.

Data Management and Quality Assurance

• Contribute to the definition and establishment of data management and data quality standards. Ensure that all data is well-managed to build stable, reusable, and quality-assured data assets, supporting long-term business needs.

Agentic-ready data products (structured and unstructured)

• Help build the data foundation of the agentic transformation. Collaborate with data scientists and business subject matter experts to enhance existing structured data products and pioneer the development of unstructured data products - making them ready for GenAl integration and advanced analytics use cases.

Data Protection and Compliance

• Ensure that all data products adhere to established data protection and compliance standards. Implement effective data access management policies, data privacy policies, and secure provisioning of data in accordance with corporate guidelines.

Continuous Framework Enhancement

• Continuously improve and enhance implementation frameworks based on the evolving needs of analytics products that consume the data assets under your responsibility.

Team Guidance and Task Management

• Provide guidance to other data engineers, both internal and external, ensuring that all team members apply consistent design principles and maintain high code quality. Break down larger work packages into manageable tasks to facilitate efficient project execution.

Metadata Management and Data Lineage

• Architect and maintain comprehensive metadata frameworks that support seamless data discovery, governance, and traceability.
• Implement automated data lineage tracking to ensure transparency and control across all data assets.