JobID=1c
YOUR TASKS
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.
HunkemöllerAcademy: 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.
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