Rihan Saifi

I’m a Data Engineer with hands-on experience designing ETL/ELT pipelines, enterprise data models, and incremental (CDC-style) processing on Azure and Databricks. I focus on reliable ingestion from heterogeneous sources and on keeping data accurate, well-governed, and traceable.

At Inmorphis, I designed and maintained a centralized CMDB data platform by building ServiceNow Discovery pipelines across on-premise and Azure sources (VMs, Resource Groups, Load Balancers, Storage Accounts). I implemented incremental data collection and reconciliation logic to detect and merge inserts, updates, and duplicate records, and I built automated data quality and validation checks to diagnose and resolve recurring failures.

In my projects, I’ve delivered both batch and streaming solutions—an Azure & Databricks medallion pipeline with Unity Catalog and MERGE INTO upserts, and a low-latency streaming fraud detection pipeline using Kafka and Spark with rule-based validation. I’m also comfortable orchestrating workflows with Apache Airflow and building governed reporting layers in Databricks SQL.