I'm an Analytics Engineer with 5+ years of experience building and maintaining production-grade data platforms. I currently work at Maya Philippines (fintech), where I lead dbt-based pipeline development supporting 40+ models and 12 ML models in production. My work spans the full analytics engineering stack, from raw ingestion to clean, tested, documented data marts that business teams and data scientists can actually rely on.
What I work with:
dbt · SQL · BigQuery · Snowflake · Dagster · Databricks · PySpark · Airflow · GitLab CI/CD · AWS · Python
What I actually do:
Design and build modular dbt pipelines (staging, intermediate, and mart layers) with proper testing, documentation, and CI/CD
Write complex SQL: CTEs, window functions, aggregations, query optimization, partitioning and clustering
Build and maintain orchestration workflows using Dagster and Airflow
Implement data quality frameworks: not-null, uniqueness, referential integrity, custom range tests
Work within Git-based development workflows: branching strategies, MRs, versioning, and deployment pipelines
Translate business questions into clean, reusable data models
How I work:
I'm async-first, communicate clearly and proactively, and don't need hand-holding. I write documentation as part of the work, not as an afterthought. If something's unclear in the brief, I ask upfront, not after I've built the wrong thing.
I'm a good fit for employers who have high standards, know what good data work looks like, and want someone who operates like a senior engineer rather than just a task-taker.
