I build reliable data platforms, BI dashboards, and analytics products that turn complex operational data into decision-ready insights.
I work at the intersection of data engineering, BI, and DevOps. My work includes production Tableau dashboards, SQL/AWS data pipelines, analytics automation, data validation, and ML-powered decision support for large-scale engineering environments.
One coherent profile across BI, analytics, data engineering, and data platform work.
Designing Tableau and Power BI dashboards, defining KPIs, improving data quality, and turning complex datasets into clear insights for stakeholders.
Exploring business and operational data, finding patterns, building reports, and translating analysis into practical recommendations.
Building reliable pipelines, SQL models, AWS-based data flows, and governed datasets for analytics and reporting.
Improving reliability, automation, deployment workflows, monitoring, credential handling, and operational stability for analytics platforms.
Carbon is an analytics product that helps users find the greenest EU countries and AWS regions, compare AWS services on cost and carbon, and explore the dashboards through an integrated AI chatbot.
An interactive dashboard ranks EU countries by carbon intensity so users can see which regions are greenest for digital workloads.
Users explore AWS regions side-by-side on carbon emissions, helping them pick low-carbon regions for their workloads.
A dedicated AWS service comparison surfaces options that are both cheaper and greener, so users don't have to trade cost for sustainability.
An integrated AI assistant answers user questions about the dashboards, regions, and comparisons in plain language.
Carbon connects data engineering, BI dashboards, AI-assisted exploration, and sustainability into one product. It helps engineers and decision-makers pick cloud regions and services that are both cost-efficient and lower-carbon.
Try the EU country and AWS region dashboards, run a cost-vs-green comparison, and ask the AI chatbot about the data.
Selected work across BI dashboards, data platforms, ML analytics, and automation.
Designed and deployed a production Tableau dashboard to monitor 6+ global compute clusters, giving engineering and IT stakeholders visibility into resource allocation, memory usage, capacity patterns, and operational health.
Problem: Cluster and resource usage data was difficult to interpret across locations.
Solution: Built a centralized Tableau dashboard backed by SQL/Athena data models and validation logic.
Impact: Improved visibility into cluster performance, supported operational decision-making, and maintained 100% data integrity during a database migration.
Tools
Built analytics capabilities to track job statistics, workload behavior, user activity, and cluster performance across compute environments.
Problem: Operational teams needed better visibility into workload patterns and recurring data quality issues.
Solution: Implemented analytics queries, fixed critical dashboard bugs, improved date filtering, and cleaned obsolete data visibility.
Impact: Improved dashboard reliability, enabled better workload analysis, and supported multi-cluster operational tracking.
Tools
An analytics product that ranks EU countries and AWS regions by carbon emissions, offers a cost-vs-green comparison for AWS services, and includes an AI chatbot that answers user questions about the dashboards.
Problem: Engineers and decision-makers struggle to choose cloud regions and services that are both cost-efficient and low-carbon.
Solution: Built interactive dashboards comparing EU countries and AWS regions, a cost-vs-green AWS service comparator, and an integrated AI chatbot for natural-language exploration.
Impact: Helps users pick greener AWS regions and services without giving up cost-efficiency, with self-serve answers via the chatbot.
Tools
Maintained and improved an enterprise reporting platform by automating cloud storage processes, validating data sources, rotating credentials securely, and improving ingestion efficiency.
Problem: Reporting platforms require reliability, secure access, clean ownership, and stable data refresh processes.
Solution: Used automation workflows, Lambda-based secret handling, data source tagging, and validation routines.
Impact: Improved platform reliability, reduced operational effort, supported cost optimization, and maintained credential security.
Tools
Built an ML-powered analytics system to predict optimal compute resources for job submissions and support better resource planning.
Problem: Users needed better guidance when selecting compute resources for engineering workloads.
Solution: Implemented feature engineering, vectorization, clustering, confidence scoring, and an authenticated interactive dashboard.
Impact: Moved from static reporting to dynamic analytics and improved dashboard performance by 95%+.
Tools
Developed predictive models to analyze project and milestone delay patterns using project management data.
Problem: Project delay risk was difficult to analyze consistently due to missing dates and varying milestone structures.
Solution: Created fallback date logic, engineered milestone and duration features, and tested Random Forest-based feature selection and prediction approaches.
Impact: Produced reusable delay modeling logic and feature insights for schedule-risk analysis.
Tools
Analyzed engineering tool performance data to identify patterns, bottlenecks, and improvement opportunities for compute and design teams.
Problem: Tool test results and logs needed to be translated into understandable performance insights.
Solution: Integrated log-based data sources, explored performance patterns, and prepared dashboard-ready insights.
Impact: Helped surface bottlenecks and supported data-backed optimization discussions.
Tools
Personal projects covering Power BI, Tableau, SQL, and data analysis fundamentals.
Interactive Power BI dashboard demonstrating data modeling, report design, and business intelligence storytelling. Shows hands-on Power BI experience alongside my primary Tableau work.
Tableau dashboard analyzing Amsterdam Airbnb listings to surface pricing, location, availability, and market trends.
Excel-based analysis using cleaning, pivot tables, charts, and regional sales insights.
Comprehensive data cleaning project using MySQL on a world layoffs dataset. Demonstrates advanced SQL techniques for handling missing values, duplicates, and data standardization.
Python-based web scraper that monitors Amazon products and sends notifications for price drops. Demonstrates web scraping, data handling, and automation techniques.
Practical experience across the BI, analytics, data engineering, and platform stack.
Stakeholder dashboards, KPI design, and reporting at scale.
Reliable pipelines, governed datasets, and analytics-ready models.
Turning operational data into decision-ready insights.
Reliability, automation, and operational stability for analytics platforms.
Predictive models supporting analytics and decision support.
8+ years of progressive experience in data
NXP Semiconductors
Leading data analytics, ML, and DevOps initiatives for HPC cluster management and job prediction systems
Techno Teams
Analytics and data-driven insights for marketing and sales optimization
ABN AMRO Bank N.V.
Research and stakeholder analysis for business and IT alignment
Techno Teams
Technical Writing & Content Strategy Department
Notes on BI, analytics, data engineering, cloud / DevOps, and sustainability analytics.
A practical deep dive into how Atomicity, Consistency, Isolation, and Durability are implemented across databases, lakehouses, and distributed systems.
What turns a dashboard from a chart collection into a tool stakeholders actually trust and use to make decisions.
Lessons learned across pipelines, modeling, and dashboard design when shipping analytics products that drive real decisions.
Open to BI, Data Analyst, Data Engineer, and Data Platform opportunities.
Looking for someone who can connect dashboards, data pipelines, analytics, and platform reliability? Let's connect.
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