Emran Ford

I’m a highly experienced Data Engineer and Cloud Data Platform Architect with 10+ years designing, developing, and operating scalable, cloud-native data platforms. I build end-to-end batch and streaming pipelines (ETL/ELT), modernize legacy warehouses, and optimize cloud costs while improving data quality for analytics and AI/ML.

In my current role, I’ve designed and developed cloud-native platforms using AWS, Snowflake, Databricks, Delta Lake, and dbt to support analytics, reporting, AI/ML workloads, and real-time data products. I architected real-time streaming pipelines with Kafka, Spark Structured Streaming, and cloud-native event services to enable near real-time dashboards, alerts, and operational insights, while optimizing performance through partitioning, clustering, compaction, Z-ordering, and workload tuning.

I also focus on reliability and trust: I’ve implemented data quality and observability frameworks using Great Expectations and anomaly detection to reduce production incidents, and I’ve established governance, data lineage, metadata management, and RBAC/IAM controls for secure, auditable data assets in regulated environments. I partner across product, analytics, data science, security, and business teams, and I mentor junior data engineers while contributing to long-term platform strategy and roadmap execution.