Senior Data Engineer

at  JYSK

JOB DESCRIPTION

Are you passionate about data, analytics, and AI? Do you have an extensive experience in data engineering and want to contribute to a fast-growing international retail company that’s leveraging data-driven solutions to transform its business? If so, we want to hear from you!
At JYSK, we recognise the importance of AI and Analytics in maintaining our position as a leading retailer. We see a huge potential in leveraging technology to enhance customer experiences, increase sales and boost profitability - ultimately making life better for our customers and employees.
We are seeking a highly skilled and experienced Senior Data Engineer to join our Advanced Analytics and AI team, where you’ll work with six passionate colleagues dedicated to data, analytics, and AI.

ABOUT US

We believe that our employees are key to our success going from one store in 1979 to more than 3,300 stores worldwide today. That is why we strive to offer development and possibilities of growing within JYSK, and we also take pride in rewarding engagement and a great effort among our employees. Our three fundamental JYSK Values – Tradesman, Colleague and Corporate Spirit – express the behaviour and attitude that we can expect from each other. We trust each other, and we believe in delegation and freedom with responsibility.
JYSK wants to include everyone, no matter the age, gender identity, race, sexual orientation, physical or mental ability, ethnicity, and experience. Together, we secure our inclusive culture that encourages, supports, and celebrates the diverse voices of our employees. Because a great mix of minds, talents and unique personalities makes us a stronger team.
For more information, please visit our career page.

• Design, develop, and maintain data pipelines and architectures for AI and analytics projects.
• Create and maintain automated data ingestion, transformation, and validation.
• Ensure data quality, integrity, and security across all data systems.
• Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver effective solutions.
• Implement data management best practices, including data governance and compliance with relevant regulations.
• Monitor and optimise system performance to ensure efficiency and scalability.
• Support the integration of new data sources and ensure smooth data flow across systems.
• Stay up to date with industry trends and emerging technologies in data engineering and cloud computing