Ehmad Aslam

I’m a results-driven Data Engineer with 7+ years of experience building and scaling production-grade data platforms across ecommerce and logistics SaaS. I bring deep expertise in Python, SQL, dbt, Databricks, and PySpark, and I’m comfortable shaping end-to-end data systems that reliably power analytics outcomes.

At Reveel Group, I architected and maintained end-to-end ELT pipelines ingesting 100M+ parcel invoice records per month from UPS, FedEx, and DHL carrier APIs and EDI feeds. I migrated legacy monolithic SQL transformations to dbt, delivering 200+ modular, versioned, and tested data models on top of Delta Lake—reducing pipeline failures by 40% and cutting feature development cycle time by 30%. I also built high-throughput PySpark jobs on Databricks for multi-carrier contract data and engineered the Finance Automation pipeline that eliminated ~15 hours/week of manual reconciliation.

I’ve also built the real-time and warehousing backbone that makes operational and analytics teams faster. As a Junior Data Engineer at Spreetail, I developed Kafka-based real-time streaming pipelines across 20+ marketplace platforms, and I designed Snowflake data warehouse models to consolidate order, inventory, and fulfillment data. I orchestrated pipelines with Dagster for lineage and observability, and used Airbyte connectors to standardize ingestion into AWS S3—significantly reducing time-to-integration for new sources.

I’m especially proud of the engineering rigor behind the work: I implement layered data quality frameworks (dbt tests and Great Expectations), enforce data contracts and pipeline SLAs, and optimize Spark performance through partition tuning, caching, and cluster autoscaling. I mentor junior engineers and interns on Databricks workflows, dbt best practices, and PySpark development—and I’m certified in Databricks and dbt Analytics Engineering.