Lead Data Engineer

We are looking for a highly skilled Lead Data Engineer of our Analytics and AI team to drive the implementation of a new centralized data analytics hub. This platform will serve as the foundation for reporting, analytics, AI, and marketing activation initiatives across the organization. You want to put your deep understanding of data engineering practices, cloud technologies, and AI ops to good use by building this new hub. Working closely together with several other teams directly using the data we provide, we rely on your superb communication skills to foster that connection and collaboration. You will be part of our Analytics and AI team, working with Google cloud as our central hub for all data products. You will lay foundations of way of working of the data engineering team in the data department in close collaboration with our Data Integration and Data Operation teams.

As the Lead Data Engineer of the Analytics and AI team, you will be the pragmatic and technical leader driving the creation and evolution of our analytical data hub. You will define standards and a best practices that enables the team to accelerate the delivery of analytical use cases. Your ability to translate complex data requirements into robust data pipelines that deliver the right assets at the right time will be crucial for success.

We expect you to:

• Define and implement data solutions, such as data pipelines, data models, data marts, and AI models
• Provide guidance and support to data engineers and developers in building and deploying data solutions, reviewing and optimizing the solutions for performance, quality, and security
• Collaborate with business stakeholders to deliver data solutions
• Leading and growing the team experience in terms of best practices for data pipelines
• Set-up operational alignment with data governance to proactively flag data quality issues
• Translate required functionality into the right tools that fit with the vision for the platform, the future plans of Rituals, and the existing environment

Requirements

• Proven experience in designing and implementing and operating complex data pipelines at scale
• Strong knowledge of cloud platforms and tools. Notably Google Cloud together with BigQuery, Airflow, Dataflow / DBT.
• Expertise in data modeling, data warehousing, pipelines and data governance
• Experience with data visualization tools (PowerBI, Looker, or similar)
• Strong understanding of AI and machine learning concepts and how to deploy ML solutions (ML ops design principles)
• Excellent communication and stakeholder management skills
• A Bachelor’s degree in Computer Science, Information Technology, a related field or equivalent professional certification
• Minimum of 5 years of relevant work experience

Grow with us and please apply via the website! The next steps are:

• Our recruiter will contact you within 10 working days
• An introductory meeting with a team member and the hiring manager follows
• A second interview where you will give a presentation
• In the event of a positive outcome, you will receive a proposal with the terms of employment

Any questions? Let Lars know via [email protected]