Self-service data-quality platform
Designed a self-service platform for defining, running, monitoring, and investigating data-quality checks across distributed data workloads.
Almere Β· NL
8+ years shipping production systems end-to-end, from distributed data infrastructure to multi-agent LLM platforms and full-stack microservices.
Designed a self-service platform for defining, running, monitoring, and investigating data-quality checks across distributed data workloads.
Designed an AI-assisted review workflow that checks proposed event schemas against documented contracts and produces a structured, evidence-backed review.
Designed Model Context Protocol integrations that give AI agents structured access to location, routing, and traffic-analysis capabilities.
Contributed to an agent toolkit that lets LLM applications interact with mapping capabilities through structured, typed tools.
Designed a multi-agent prototype for answering traffic-analysis questions with scoped tools, structured evidence, and a single grounded response.
Designed a planner-executor system that converts natural-language location requests into grounded, multi-step tool calls and explainable results.
Refactored event-processing pipelines into a governed, queryable transformation layer for trusted operational analytics.
Refactored a fragmented set of analytics pipelines into a reusable Python template with consistent ingestion, transformation, testing, and operational behaviour.
Built a typed API layer that turns analytical warehouse queries into reliable, self-service usage reporting for product and support teams.
A practical pattern for turning scattered technical knowledge into queryable metadata: stable identities, version history, clear ownership, and views people can actually use.
Dashboards usually reveal a data problem after it has travelled through half the platform. Data contracts move the conversation upstream: clear schemas, ownership, compatibility rules, and a better way to change pipelines.
Watermarks, exactly-once, and stream-stream joins each have a sentence in the docs and a paragraph of corner cases in production. Here's the gap between what the API says and what bites you at 3am β across Flink and Spark Structured Streaming.
How to make a 2-minute walkthrough of a search system with React, Remotion, and Claude Codeβplus the small set of habits that made the process work.
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