Harish Ravi

I’m a data engineer with 8+ years of experience building production-grade data platforms and analytics-ready data products. I turn fragmented source systems and high-volume operational data into trusted, well-modeled outputs that support reporting, automation, machine learning, and business decision-making.

I’m at my best when the problem is messy—sources are inconsistent, requirements move fast, and the business still expects the data to be accurate, fast, and dependable. I don’t see data engineering as “moving data”; I design for downstream usability, long-term maintainability, and production reliability as analytics, AI, and operational demands grow.

In my recent work at Accenture (Senior Software Engineer / Data Engineer), I designed and maintained Python- and SQL-based ETL/ELT workflows feeding analytics, automation, and AI-oriented use cases. I built cloud-native batch, incremental, and near-real-time pipelines with schema-change resilience, monitoring/recovery logic, and strong data quality checks (freshness, completeness, duplicates, null-rate shifts, schema drift, and anomalies).

At IBM (Senior Software Engineer / Data Platform Engineer) and Crescent Financial Systems (Software Engineer / Data Engineer), I strengthened warehouse-friendly modeling (star/snowflake-style dimensional structures), improved performance through tuning and refactoring, and supported ML by preparing model-ready datasets and reliable data access patterns. I consistently focus on observability, lineage awareness, and operational resilience—because analytics and ML are only as good as the consistency of the data behind them.