Get notifications about new remote jobs right in your browser! › 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.
Lead data platform, SQL optimization, and analytics infrastructure initiatives across Azure, AWS, PostgreSQL, SQL Server, Azure SQL Managed Instance, ClickHouse, and hybrid operational environments. Design and support SQL-based transformation workflows, analytics-ready data models, and reporting datasets. Optimize SQL workloads, database schemas, indexes, stored procedure patterns, and query logic. Support Azure-based data engineering workflows involving Azure Data Factory, Azure Functions, Azure DevOps CI/CD, cloud-hosted databases, and Git-based deployment processes. Automate workflows using SQL, Python, PowerShell, Bash, Git, Azure DevOps, Jenkins, and Terraform. Troubleshoot production data issues, pipeline failures, performance bottlenecks, blocking/deadlocks, reporting delays, and database reliability incidents. Mentor data engineers and DBAs.
Supported SQL Server, PostgreSQL, MongoDB, Azure SQL Managed Instance, Azure, and hybrid database environments. Developed, tuned, and optimized SQL/T-SQL queries, indexes, database maintenance routines, and reporting workloads. Supported modernization initiatives including migration planning, schema validation, workload tuning, backup validation, and cloud-hosted data architecture. Troubleshot production performance issues and supported operational reporting and data integration workflows using SSIS, Power BI, SQL-based transformations, and validation checks. Automated backup, recovery, validation, and operational workflows, reducing supported PostgreSQL RTO to under 15 minutes. Integrated Prometheus and Grafana monitoring, reducing MTTR by approximately 40%.
Focused on enterprise database reliability, performance optimization, and HA/DR design across client environments. Designed and maintained SQL Server environments with Always On, WSFC, Log Shipping, and Replication. Performed performance tuning, indexing strategy design, and capacity planning. Automated backup and alert workflows and supported early cloud migration initiatives to Azure.
Designed and maintained database security and recovery frameworks. Implemented structured maintenance plans aligned with Microsoft best practices. Managed incident response for critical SQL Server events.
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