Mukesh V
Data Engineer
Mukesh is a Data Engineer at Algoscale building the deep-plumbing pieces of enterprise data platforms across AWS and Azure — MDM ledgers, CDC pipelines, Lake Formation access controls, Fabric semantic models. Writes from the production side of the stack.
7 articles
Data Lake or Data Swamp: 3 Failure Modes
Most data lakes drift into swamps within 18 months. A practitioner's breakdown of three failure modes — zones, governance, lifecycle — and the fixes.
Watermark Bugs in Fabric Incremental Loads
A watermark incremental load in Microsoft Fabric silently duplicated 3 months of Gold-layer data. The fix: idempotent MERGE plus a row-count assertion.
Beat NetSuite API Limits with SuiteQL
Our NetSuite pipeline hit API rate limits and ran 28 hours per ingestion. Moving from the REST record API to SuiteQL cut it to under 6. Here's exactly how.
Lakehouse vs Warehouse vs Data Lake
Lakehouse, warehouse, or data lake? A 2026 practitioner's decision framework that picks by workload concurrency, latency, team skill, and cost shape.
Medallion Architecture: 5 Failure Modes
Most bronze/silver/gold lakehouse builds repeat the same five mistakes. A practitioner's breakdown of medallion architecture failure modes — and the fixes.
Iceberg vs Delta vs Hudi in 2026
After years of open table format wars, the 2026 picture is clear: Iceberg has won, but the catalog choice is now where vendor lock-in lives.
Serverless MDM: Lambda + Postgres on AWS
A production MDM pattern with Lambda + RDS PostgreSQL. Multi-ERP canonicalisation, ledger-hit caching, sub-50ms enrichment - without Profisee or Tamr.