Leyba Ford

I’m a Staff Data Engineer with one decade of experience designing and delivering scalable data platforms and analytics solutions. I focus on cloud-based data engineering, robust ETL/ELT pipelines, and data modeling that improve performance, reliability, and scalability across enterprise environments.

At Klue, I architected and scaled enterprise-grade data platforms for analytics, AI/ML workloads, operational intelligence, and real-time business decision systems. I built batch and streaming pipelines with Python, SQL, PySpark, Kafka, Spark Streaming, and CDC frameworks, and I led migrations to lakehouse architectures using Snowflake, BigQuery, Azure Synapse, and Databricks.

I also optimize for measurable outcomes and operational excellence. I implemented enterprise data governance (data lineage, schema evolution, metadata management, PII handling, RBAC, and data quality monitoring), and I improved SQL workload performance by reducing query execution times by over 40% while significantly lowering cloud infrastructure costs. I delivered CI/CD deployment pipelines using Azure DevOps and GitHub Actions, and I enhanced platform observability with automated monitoring, alerting, logging, and incident response practices.

Earlier, as a Senior Data Engineer at PocketHealth, I developed cloud-based data integration and transformation workflows using AWS/Azure, Snowflake, MongoDB, PostgreSQL, Azure Data Lake, and dbt. I built real-time streaming pipelines with Kafka and Spark Structured Streaming, supported BI (Power BI, Tableau, Looker), and strengthened reliability and governance with validation and automated quality controls. I hold a Bachelors in Computer Science, along with AWS Certified Data Analytics – Specialty, Snowflake SnowPro Core, and Databricks Certified Data Engineer Professional.