Data Engineer specializing in financial data pipelines, revenue recognition automation, and BI reporting for fintech and e-commerce.
I design and optimize scalable data pipelines that bridge complex upstream production systems with downstream financial reporting — the kind investor relations and executive leadership actually rely on. My core focus is building reliable ELT workflows using Apache Airflow and dbt, modeling financial data structures in SQL, and ensuring high-availability data marts in BigQuery, MaxCompute, and PostgreSQL.
At Gojek's Enterprise BI team, I engineered automated pipelines for revenue recognition and financial offsetting that reduced manual reconciliation effort by 80%, directly feeding SAP posting schemas while maintaining 99.9% ingestion reliability across GoPay's e-wallet and payments ecosystem.
What sets me apart:
- Deep domain expertise in financial/accounting data systems — not just generic ETL, but pipelines built for audit-grade accuracy
- Strong SQL and Python foundation backed by an Economics degree (quantitative research methods, econometrics)
- Proven track record collaborating directly with Finance, Product, and Data Platform teams to enforce data governance at scale
- Comfortable owning the full pipeline lifecycle: ingestion, transformation, orchestration, and BI delivery (Metabase, Looker Studio)
If you need someone who understands both the engineering and the financial logic behind the numbers, I can help you build data infrastructure that finance teams and executives can actually trust.