I am a senior data engineer and cloud data platform engineer with more than 9 years of experience designing, optimizing, and supporting production data platforms across Azure, AWS, and GCP-aligned environments. My background includes SQL Server, PostgreSQL, cloud-hosted databases, and hybrid infrastructure, with a strong focus on reliability, performance, and production support.
I specialize in SQL, Python, ETL/ELT pipeline development, Azure Data Factory, Databricks, Spark SQL, PySpark, ADLS Gen2, Synapse, SSIS, dbt, CI/CD, Git, data modeling, pipeline monitoring, data quality, reconciliation, and automation. I have built scalable data pipelines, transformation layers, validation checks, reporting datasets, and analytics-ready models for business-critical workflows.
In my recent roles, I have led data platform and SQL optimization initiatives, improved deployment validation and operational runbooks, and strengthened the supportability of cloud data pipeline releases. I have also worked on query tuning, schema optimization, stored procedure refactoring, indexing strategies, and production incident troubleshooting to improve reporting stability and reduce manual effort.
I have experience supporting database modernization and reporting platform scalability across SQL Server, PostgreSQL, Azure SQL Managed Instance, and cloud-hosted services. My work has included migration planning, backup validation, workload stabilization, source-to-target checks, and observability improvements using tools such as Prometheus, Grafana, and Azure Monitor.
I enjoy collaborating with engineering, DevOps, operations, product, and business stakeholders to translate reporting needs into reliable data solutions. I also mentor data engineers and DBAs on cloud data architecture, monitoring, SQL optimization, and production-grade engineering practices.
I am based in Nairobi, Kenya, and I am open to remote work and US shift schedules. My career reflects a strong combination of hands-on engineering, operational ownership, and continuous improvement across data platforms, databases, and analytics infrastructure.
