This position is for a Senior Data Engineer to lead the design and implementation of Hunkemöller's enterprise data warehouse and data mesh on Google Cloud. You will guide and mentor a team of internal & external engineers, owning and driving key data transformation initiatives. The right candidate will be excited by the prospect of architecting and building a new, scalable data platform from the ground up to support next-generation analytics and AI initiatives.

Responsibilities:

• Architect and Build Data Pipelines: Design, develop, and own robust, scalable data pipelines using SQL and cloud technologies (GCP), ensuring the highest standards of data quality, reliability, and performance.
• Lead Data Modeling & Warehousing: Lead the design and implementation of scalable data models (e.g., star schemas, data vaults) within our enterprise data warehouse (BigQuery), ensuring they are optimized for analytics and BI consumption.
• Own GCP Data Services: Drive the design and implementation of our Google Cloud Platform (GCP) data infrastructure, focusing on automation, data delivery, security, and scalability improvements.
• Mentor and Collaborate: Partner with Product, Data, and Design teams to resolve complex technical data issues. Mentor junior engineers and guide the team on data engineering best practices.
• Contribute to Data Governance: Help establish and enforce data governance standards, data quality frameworks, and best practices across the data platform.
• Build for Analytics & AI: Build and optimize data platforms that power our BI, Data Science, and AI solutions, ensuring data is accessible, reliable, and ready for analysis.

Requirements:

• Extensive Data Engineering Experience: 5+ years of hands-on experience in data engineering, with a proven track record of designing and implementing large-scale data pipelines and data warehouse solutions.
• Expert SQL Proficiency: Expert-level skills in writing complex, highly-optimized SQL queries for data manipulation and analysis.
• Cloud & Data Warehousing Expertise: Deep knowledge of cloud data services, preferably on Google Cloud Platform (BigQuery, Dataflow, etc.).
• Strong Programming Skills: Experience with OOP concepts (Python preferable) and applying those principles to build robust data engineering solutions.
• ETL/ELT Architecture: Extensive experience architecting and building ETL/ELT systems. Experience with dbt is a strong plus.
• Code Quality & Version Control: Proficient in writing clean, well-documented, and tested code, with strong experience using Git.
• Leadership Potential: Experience mentoring junior engineers and leading technical discussions is highly desirable.
• English Proficiency: Excellent written and verbal English communication skills.

Benefits

• 25 Days of Annual Leave: As a full-time employee, you will receive 25 days of paid holiday each year, with the flexibility to buy or sell up to 4 additional days to meet personal needs.

• Hybrid Work Model: We offer a flexible hybrid work environment, enabling you to seamlessly balance office and remote work to enhance productivity and work-life balance.

• Work From Abroad: Take advantage of the opportunity to work remotely from abroad for up to 2 weeks annually.

• International Work Environment: Join a dynamic, global team that fosters collaboration and cultural diversity, providing you with a rich and inclusive professional experience.

• Partial Travel Allowance: Benefit from a partial travel allowance to support your commuting costs, ensuring your journey to and from work is more affordable.

• Hunkemöller Academy: Gain access to our Hunkemöller Academy, offering a wide range of professional development programs to support your career growth and skill enhancement.

• Employee Discounts: Enjoy a 25% discount on all company products, allowing you to access our offerings at a reduced price.

Apply now with your CV (in English) or LinkedIn profile only.

For this role, we're not looking to work with external agencies.