Master Operations Research
Wageningen University & Research Centre
Additional courses: (Advanced) Econometrics, Statistics, Decision Science
Award winning master thesis (Winner VEDIS Retail Thesis Award 2016)
Introduction
Bart is widely experienced and deeply interested in the world of data. With years of work experience in various roles within the data domain, including as lead developer, data engineer and data analyst, he is a broadly experienced data specialist.
Due to the combination of his fast learning ability, analytical and pragmatic way of thinking and social skills, he functions well within a team, but he is also effective independently. He has more than 5 years of experience with Python, SQL & PowerBi, supported by several years of cloud experience (several Azure components & Google BigQuery). While working as a python developer and data engineer, Bart is well versed with various big data technologies such as Airflow, Spark, Kubernetes, Hadoop & Hive. With a background in Operations Research and a focus on econometrics, he is also familiar with the design and deployment of various data science models that must be able to run robust and scalable in production.
Besides his work, he loves music, concerts and sports (cycling, indoor football, padel). A drink afterwards should certainly not be skipped.
Recent Jobs
Data Engineer - Waterschap Brabantse Delta
Jan 2023 – now
Data Engineer
Building an Azure cloud-based DataLab and bringing multiple on-premises data sources to the cloud.
Lead Developer - Deapr
April 2022 – December 2022
Lead developer
Responsible for the development of the Godeapr® application that recognizes 30 different types of personal identifiable information in unstructured file systems (pdf, mail, word, pptx, images, etc.) or structured databases (MySQL, PostgreSQL, Oracle, etc.). Responsible for a team of 3 developers regarding the frontend, backend, algorithms, design, deployment, security, testing and quality of the OS-independent application. Including intensive use of: OCR, multiprocessing, string matches, regular expressions, dictionary matching, correctness algorithms.
Tools & Techniques:
- Back-end is completely written in Python with Cython enhancements.
- Front-end is written in NodeJS / Typescript, using Angular / Electron.
- Structural databases: PostgreSQL, MSSQL, MySQL, SQLite, Oracle, MariaDB
- Docker for database setup and testing
- Azure DevOps for building, testing & deployment and project support (scrum)
Available in the mac app store and the windows app store. Check it out!
Date Engineer - Rabobank
July 2020 – March 2022
Data Engineer
Responsible for the development and operationalization of the Advanced Analytics platform with 180 users (on premise and in the Azure cloud) where advanced models and algorithms are developed for various data science projects; KYC, transaction monitoring, transaction categorization, forecasting models, Rabo Research, Risk
- Installing stable Airflow environments and connect (ETL) dozens of different sources within the bank
- Creating and migrating ETL jobs to Airflow and Azure Data Factory in Python, SQL and Bash
- Developing deployment pipelines in Azure DevOps (Terraform)
- Managing data and platform related authorizations in a Hadoop cluster to minimize security risks
- Designing and developing functionalities in Python and Bash that clean up the platform and make it more secure
- Improving the platform by making new technologies available (PySpark, SparkSQL) within Dataiku for Data Scientists
- Provide operational support to various Data Science projects
- The platform consists of the following components:
- Cloudera Hadoop cluster (55 Linux Red Hat servers)
- Sqoop / HIVE / Impala (data analyses / transformation)
- Spark / PySpark (data processing / transformation)
- Kubernetes (scalability)
- Dataiku (data science visualization and collaboration tool)
- Airflow (ETL / automation)
- Azure Data Factory / Azure DevOps (ETL / CI/CD)
Data Engineer / Analyst - fonQ
September 2019 – July 2020
Data Engineer / Analyst
Designing and developing a new Data Lake and associated Data Warehouses and Data Marts by means of automated data flows (Google Cloud BigQuery in combination with Airflow) and making commercial results visible in PowerBI based on this data.
- Creating and migrating ETL jobs to Airflow in Python and SQL making data available in data warehouses and data marts
- Developing and implementing a reporting environment (PowerBi) that is used organization-wide to make better data-driven decisions
- Improving the up- & cross-sell by developing insights via dashboards (PowerBi) based on the behavior of the website visitor (Google Analytics raw data)
- Development of algorithms in Python to realize better product suggestions based on these insights and a utilization rate of 100%
- Setting up and improving the order forecast in Python using SARIMAX & Random Forest models
IT Consultant - OMP
August 2016 – August 2018
IT Consultant
Responsible for the implementation of OMP+ software at global customers (Shell, Friesland Camping, IFF). OMP+ is an application for supply chain planning, demand forecasting, production scheduling and S&OP.
- Matching the OMP+ data science functionalities to the needs of the customer
- The installation (cloud-based) and configuration of the application and setting up a multi-user environment
- Designing and developing additional functionalities based on customer needs (e.g. price-based forecasting for Shell)
- Setting up and configuring the interface between different systems (SAP – OMP) including master data analysis and validation
- Analyzing current and designing future planning cycles