Koen Vantomme

Aware is a spinoff company from the French retailer group “Les Mousquetaires” , including retailers like Intermarché. The goal of Aware is to provide a web based data platform with advanced analytics to the suppliers and the retailers based in Europe to exchange sales performance data in the retail shops.

Main Responsibilities:

• Build a dwh and BI solution on top of the data platform using data vault for the KPI website.

• Work with multiple Scrum teams on launching a product in Portugal, ensuring correct solutions through information exchange, and alignment on priorities.

• Strong collaboration among analysts, developers, and stakeholders; manage product visions, roadmaps, and backlogs.

• Scrum Community Management: Conduct sprint planning, execution, and agile ceremonies; communicate with stakeholders about progress and challenges.

• Utilize Miro for visual collaboration; define project performance metrics (capacity and velocity).

• Team Coaching: Mentor new Product Owners, providing feedback and support during planning and ceremonies.

• Assist in development and testing on Azure Cloud and Databricks Notebooks and SQL Server and Data Vault Modelling

• KPI definitions and implementation in Power BI

• Data Industrialisation ( data quality, data governance)

Quandoo, based in Berlin, is building a platform to help restaurants with table reservations. They are established in 12 countries and are having a profitable business. In 2020 they moved from AWS to GCP platform. Due to Corona they had to let go a lot of employees and suddenly there was no data engineering team anymore. I helped Quandoo to manage the data infrastructure and pipelines during the pandemic. I also helped to recruit a new data engineering team and helped to establish a new mission statement for the data engineering team. At the same time we fixed a lot of the current data issues and improved the data infrastructure. Quandoo is using Scala applications for data ingestions, the plan is to move away to Python. Alle pipelines are running on the Google Kubernetes engine. For data transformations they are using a combination of Python and DBT. Big Query is the central database. Data is being offloaded from Kafka into GCS/BQ. DBT is transforming the data in data marts and is the central tool for data processing. Another important task was to shutdown the legacy Redshift and migrate all data to GCP. All CI/CD is done in Gitlabs. We worked also on the improvement and alerting of the data pipelines. Another important achievement was that we were able to modernize DBT. Before they were using a forked old DBT version. We went away from the DBT fork and we can now follow the standard DBT software release process. In this role I mainly worked as data engineer , I also took up extra responsibilities as Team lead and Product owner and Scrum master.