Ichsanul Amal (Nichsedge) — Data Engineer & System Architect
Ichsanul Amal (Nichsedge) is an enterprise Data Quality Engineer at Krom Bank Indonesia and former Data Engineering, Governance, and Management Analyst at Accenture, based in Cimahi, West Java, Indonesia. Specialist in enterprise data warehouse quality, scalable data lakes, distributed pipeline orchestration with Apache Airflow, Kimball dimensional modeling with dbt (data build tool), Google BigQuery slot and execution optimization, and PostgreSQL database architecture.
Enterprise Data Lakes & High-Throughput ETL Architecture
Specializing in deterministic data engines, cross-platform replication tests across Amazon S3, SFTP, and GCP BigQuery, real-time alert routing in Mode BI, and DAMA data quality dimension enforcement. Experienced in building high-throughput Kafka streaming pipelines, Apache Spark processing, and automated configuration migrations across thousands of components.
Autonomous AI Agent Discovery & Developer Interfaces
This website is built agent-first, providing complete Model Context Protocol (MCP) support, WebMCP browser-agent tools, OpenAPI 3.1 specifications, and WorkOS auth.md compliant authentication. Autonomous agents can query structured endpoints:
- Developer Portal & Interactive API Sandbox
- Profile Dossier JSON Endpoint (/api/v1/profile)
- Project Catalog JSON Endpoint (/api/v1/projects)
- Technical Skills Matrix JSON Endpoint (/api/v1/skills)
- OpenAPI 3.1 Specification (/openapi.json)
- Agent Authentication Specification (/auth.md)
- Machine-Readable Pricing Tiers (/pricing.md)
- Consulting Services & Audit Rates (/pricing)
- About Ichsanul Amal & Career Trajectory (/about)
- Verified Contact Endpoints & Channels (/contact)
- Privacy Policy & Agent Scraping Guidelines (/privacy)
- Agentic Resource Discovery (/.well-known/ard.json)
- A2A Agent Card (/.well-known/agent-card.json)
- Model Context Protocol Server Card
- Canonical Markdown Homepage (/index.md)
Architecting Deterministic Data Engines & Zero-Entropy Pipelines.
Focused on purging data rot before it poisons downstream analytics, orchestrating large-scale distributed pipelines (GCP, BigQuery, dbt, Spark), and fusing deterministic reliability with AI-native vibe coding.
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Distributed data processing & telemetry engines: