Abdullah Aleem

At PartnerLinQ Systems, I design and maintain scalable data pipelines for large-scale transactional data using Databricks and Azure Data Factory.

I build incremental batch and streaming pipelines with Spark, improving processing latency and efficiency. I also apply idempotent processing and fault-tolerant design patterns to reduce data inconsistencies.

I design Medallion Architecture across Bronze, Silver, and Gold layers with Delta Lake, and optimize Spark workloads through partitioning and caching for millions of daily records.

I've also built an end-to-end Kafka, Spark Structured Streaming, and Delta Lake pipeline with event-time watermarking, checkpointing, ACID-backed writes, and duplicate-safe ingestion. My work supports reliable analytics as well as AI-ready pipelines for RAG and vector database integration.