Enabling systems to think and scale.
My work exists at the friction point between messy real-world data and clean, actionable intelligence. I specialize in building the "nervous systems" of modern organizations—the pipelines, warehouses, and streaming engines that turn noise into signal.
Professional Archive
Accenture
Data Engineering, Governance, and Management Analyst
Driving enterprise data engineering, governance standards, and data management pipelines. Partnering with cross-functional stakeholders to define metadata specifications and enforce governance rules across data lakes.
Spearheaded enterprise data quality verification and metadata governance frameworks across data platform pipelines.
Vibe Coder
May 2025 — Oct 2025Led research and prototype engineering for LLM-agent-driven applications. Evaluated cutting-edge AI developer platforms and constructed multi-agent tools to automate and streamline software development cycles.
Researched and built prototypes using agentic AI frameworks such as LangChain, AutoGen, and Google Agent Development Kit (ADK).
Evaluated and compared state-of-the-art AI developer tools (Gemini CLI, Lovable, Cursor, Cline, Replit) to automate engineering workflows.
Constructed a full-stack project management app prototype, integrating AI agents to coordinate and assist dev workflows.
Data Quality Engineer (Telecom Project)
Sep 2024 — Apr 2025Spearheaded sales and customer data quality models for a major telecommunications client. Formulated stored procedures, optimized PostgreSQL queries, and automated massive configuration migrations.
Developed customer and sales data quality dimensions models in the telecom industry.
Automated configuration migration for ~4,000 components using custom Python scripting, cutting manual effort.
Constructed and monitored Airflow DAGs for ad-hoc ETL operations and proactive system monitoring.
Created complex SQL procedures, window functions, and delivered business data marts for Tableau visualization.
Executed root cause analysis, bug resolution, and expanded UAT assertions for the core DQ platform.
Neural Technologies Indonesia
Database Engineer at Telkomsel's Project
Managed database architecture and ingestion pipelines for the Network Service Measurement unit, integrating various formats (REST APIs, CSVs, RDBMS) and introducing dbt to accelerate SQL analytics development.
Developed and optimized data models for the Network Service Measurement & Benchmarking unit.
Managed and monitored databases (BigQuery, PostgreSQL) and ETL pipelines using Airflow, improving data ingestion from various sources (databases, CSVs, REST APIs).
Enhanced PostgreSQL performance through indexing, partitioning, and window analytic functions; created multi-function, stored procedures, and maintained FDW databases.
Initiated data build tool (dbt) for modular SQL and faster development.
IR-NLP Lab CSUI
Research Intern
Researched and integrated natural language processing models to extract sentiment trends from academic feedback, designing responsive Flask applications to visualize system-wide metrics.
Analyzed and integrated student feedback data from e-learning systems using Python.
Performed aspect-based sentiment analysis and built a user-friendly dashboard to assess learning aspects.
Designed, developed, and deployed web & database applications using Flask and integrating them with data visualization tools.
Traveloka
Data Engineer Intern
Worked within the Core Data Team to design high-performance warehouse models for hotel and transport business units, optimizing resource utilization and monitoring BigQuery costs.
Implemented data warehouse models for hotel and transport BU, utilizing SQL and dbt (data build tool).
Migrated and optimized data warehouse assets using BigQuery and Python adhering to Kimball principles.
Monitored ETL pipeline and performed data backfill using Airflow.
Developed dashboards using Google Data Studio to monitor and optimize BigQuery resources.
University of Indonesia
Teaching Assistant
Coordinated lab sessions and evaluated assignments, serving as a primary academic link for hundreds of students during fundamental computing courses.
Teaching Assistant for Fundamental Programming (Python), Calculus, and Operating System courses.
Assess and assist the students with weekly lab sessions, assignment work, and assignment demos (interviews).
The "Why" Behind the Pipes.
In modern engineering, the true challenge isn't just scaling the nodes or writing faster queries—it's establishing trust in the data itself. As a Data Engineer, I build pipelines that act as the reliable nervous system of the organization.
My philosophy on data engineering is simple: ****.
Whether it is optimizing query execution times by 50% or automating the migration of thousands of system configurations, my goal is to design robust, self-healing platforms that turn operational complexity into clean, actionable insights.
Systems Thinking
I don't just build pipelines; I architect ecosystems where data flows naturally and predictably.
Pragmatic Ops
Stability is a feature. I prioritize observability and self-healing mechanisms in every build.