Senior Data Engineer - for Denmark residents only

As our new Senior Data Engineer, you will become part of our growing Data Insights and Science team. You will employ new technologies across multiple cloud platforms to help brands reach their next level in 1:1 retargeting, communication, and CRM. Your tasks include: Identify, collect, and integrate data from various sources by building high-quality data pipelines and data models for analytics and business intelligence purposes. Develop and optimize code to enable pipelines at minimum cost and ease of maintenance. Build monitoring procedures and tools to ensure solid ETL flows and data quality. Design processes and tools to correct ETL incidents. Collaborate with CRM developers, data scientists, data analysts, and product owners to ensure the supplied data supports the business initiatives. Consult our data analytics teams to ensure best practices on the technical use of data are followed. Design data architectures and collaborate in data migrations in cloud environments. You will join a team of highly skilled Architects, Data Scientists, and Consultants who are passionate about unlocking insights from data through analytics. You will also get to work closely with experts from other Technology, Creative, and Client Teams. What do you bring to the table? As a person, you have a team player mindset and an open‑minded attitude. You can communicate ideas and technical topics honestly and clearly, even to non‑experts, while respecting the views of others on the team. You are eager to understand and find solutions, allowing you to quickly adapt to changing situations and come up with new ideas. Moreover, you have: Experience in Spark, Python, Scala, or similar. Excellent SQL skills enabling large‑scale data transformation and analysis. A comprehensive understanding of cloud data warehousing, data pipelines and data transformation (extract, transform, and load) processes and supporting technologies such as Google Dataflow, Looker, DBT, EMR, CI/CD pipelines, Airflow DAGs, and other analytics tools. Experience with cloud‑based data infrastructures (Ideally GCP, but AWS or Azure would also suffice). Expertise in managing databases, including performance tuning, backup, and recovery. Solid knowledge of data quality management best practices, including data profiling, data cleansing, and data validation. Knowledge of strengths and limitations of visualization tools (e.g., PowerBI, Tableau, Looker, etc.) in terms of data modeling in the visualization tools. Understanding of versioning control tools like GitHub to manage changes related to dbt models and transformations, ensuring that changes are tracked, documented, and reviewed by the appropriate stakeholders. Knowledge of applying data governance principles, policies, and practices that ensure data accuracy, consistency, and security. Knowledge of Kubernetes would be an advantage. Personal skills: Strong desire to contribute towards keeping data tidy and well‑organized. Ability to think critically, identify issues autonomously, and propose corrective actions. Build great relationships with your team and stakeholders. WPP (VML MAP) is an equal opportunity employer and considers applicants for all positions without discrimination or regard to characteristics. We are committed to fostering a culture of respect in which everyone feels they belong and has the same opportunities to progress in their careers. #J-18808-Ljbffr