Data Platform and MLOps Engineer for reliable, auditable, business-ready data systems
Available • India, Singapore, Japan, Australia, New Zealand, Finland • Remote Worldwide
Messy data becomes a business risk when dashboards go stale, jobs fail, or model inputs cannot be explained. I build pipelines, trusted datasets, QA gates, audit trails, observability, and MLOps workflows so data arrives on time, passes checks, and supports decisions with confidence.
Fix broken pipelines, stale dashboards, and unreliable reports.
Cleaner operations, faster debugging, and fewer bad-data surprises.
Convert messy PDFs, APIs, websites, files, and logs into clean datasets.
Datasets your team can trust for reports, products, analytics, or ML.
Deploy and monitor ML workflows only after the data foundation is strong.
Models that are easier to track, explain, monitor, and improve.
Clarify what the data must support.
Map sources, failures, and trust needs.
Build orchestration, retries, and outputs.
Check freshness, schema, records, and rules.
Show what ran, passed, failed, and changed.
Deliver runbooks and handover notes.