Muhammad Ali

Led design of next-generation enterprise data platforms using Lakehouse and Data Mesh frameworks (Databricks, Apache Iceberg, Delta Lake) to enable scalable AI/ML analytics across trading, risk, and financial operations. Engineered ultra-low-latency streaming pipelines with Apache Flink, Kafka, and AWS Kinesis, reducing real-time data processing time by 65% and accelerating decision-making for traders and risk teams. Modernized legacy ETL by migrating workloads to serverless AWS Lambda and containerized Kubernetes pipelines, improving reliability and reducing compute costs. Drove governance and metadata strategies with Collibra/Alation integration, ensuring data lineage, access control, and regulatory compliance across financial data assets. Optimized Lakehouse infrastructure for ML/AI workloads, tuned compute, caching, and storage formats to accelerate model training and experimentation. Mentored 10+ engineers and built observability with Prometheus + Grafana; championed self-service

Architected and deployed enterprise-grade data warehouses on Snowflake, Redshift, and BigQuery; optimized data models and storage to deliver ~50% faster queries and scalable analytics. Built real-time streaming analytics with Kafka + Spark Streaming, reducing latency by ~60%. Automated ETL workflows using Airflow, dbt, Talend, and Informatica, cutting manual maintenance by ~30% and improving reliability. Led cloud migrations to AWS (S3, Redshift, Lambda) and GCP (BigQuery, Pub/Sub), achieving ~35% cost savings and greater agility. Established data governance and catalog frameworks with data lineage, PII masking, and metadata management to boost compliance and data discovery. Collaborated with data scientists to support AI/ML workloads.

Engineered scalable ETL pipelines using NiFi, Talend, and SSIS across finance, CRM, and operations, improving data availability and processing efficiency. Optimized PostgreSQL & MySQL performance through indexing, query optimization, and partitioning, reducing analytics load times by ~50%. Built BI dashboards in Tableau and Power BI delivering real-time KPIs. Implemented predictive analytics and data validation workflows increasing forecasting accuracy and reducing discrepancies. Strengthened data security and governance with RBAC, encryption, GDPR/SOC 2 alignment. Supported AWS cloud migration, moving on-prem processes to Redshift/S3-based pipelines.