Engineer by training, data strategist by choice. I work at the intersection of data engineering, analytics, and AI — building pipelines, dashboards, and tools that help people make better decisions. At FrieslandCampina, I lead AI initiatives in HR People Analytics, developing Genie-based assistants and exploring privacy-conscious AI for sensitive data applications. Before that, I spent three years at RoyalHaskoningDHV building ETL workflows and dashboards, and earlier worked on data-driven energy renovation tools through a TU/e PDEng programme.
Experience
FrieslandCampina · Amersfoort
- Leading AI initiatives within Global HR People Analytics, focusing on practical and secure enterprise applications of generative AI
- Developing a Databricks Genie-based HR analytics assistant that enables natural language querying of HR data (70% accuracy in testing)
- Exploring privacy-conscious AI solutions with locally-hosted open-source models for sensitive HR use cases like anonymisation
- Led migration of HR DataMarts to Azure and improved Databricks environment usability
- Rebuilt fragile automations and developed high-performance Python-based ETL workflows to overcome scalability limitations
RoyalHaskoningDHV · Amersfoort
- Developed and optimised Alteryx workflows for ETL processes, integrating data from SQL tables, Excel files, and APIs into Power BI data models
- Designed Power BI dashboards in collaboration with stakeholders across the organisation
- Led migration of corporate data to Parquet format, reducing Azure Data Lake storage costs by nearly 90% and significantly enhancing processing speed
- Integrated stakeholder feedback, managed change requests, and provided ad-hoc data analysis to support decision-making
- Participated in weekly sprints, defining goals, user stories, and tasks in Azure DevOps
Woonbedrijf · Eindhoven
- Designed a stated preference survey to collect data on tenant preferences regarding future energy renovations of their dwellings
- Applied discrete choice models in R to gain insights into tenant preferences on energy renovations
- Built a web application in R Shiny allowing decision makers to visually evaluate energy renovation packages as a function of tenant preference
- Project featured on TU/e's website
Technical Skills
Languages & Tools
Python
SQL
R
Alteryx
Cloud & Data
Azure
Databricks
ETL Pipelines
Data Lakes
Analytics & AI
Power BI
AI/LLMs
Streamlit
Genie
Salesforce
Education
PDEng, Smart Buildings & Cities
TU Eindhoven — 2022
MSc Mechanical Engineering & Industrial Management
University of Sheffield — 2020
BTech Production Engineering
College of Engineering Pune — 2018
Notable Projects
HR Analytics AI Assistant (Genie)
Databricks Genie-based conversational AI for HR analytics — enabling natural language querying of employee data with 70% accuracy in testing.
Data Lake Modernization (Parquet Migration)
Led migration of corporate data to Parquet format at RoyalHaskoningDHV, reducing Azure Data Lake storage costs by ~90% and improving query performance.
Energy Renovation Decision Tool
R Shiny web app built during TU/e PDEng at Woonbedrijf, combining stated preference survey data with discrete choice models to help housing associations evaluate renovation packages.
Languages & Interests
English — Fluent (professional)
Dutch — Fluent
Hindi — Native