Michael Imani

Data and software engineer with 3+ hands-on experience building ETL/ELT pipelines, operational dashboards, and metric infrastructure that stakeholders rely on for time-sensitive decisions.

Background spans core-banking data infrastructure, a production health-tech platform, and a data engineering bootcamp built around Airflow, Spark, Kafka, and dbt. Comfortable owning the full path from raw data to a documented, decision-ready dashboard, and back to the query logic behind it.

Data Engineer || Backend Engineer - Qare+

Cloud-native digital health platform

• Built ETL pipelines moving production PostgreSQL data (hosted on AWS) into SQL Server to power analytics dashboards in Apache Superset the team's primary source for operational reporting.
• Applied data vault modelling to structure wearable-device and AI-generated health data so it holds up for both business reporting and downstream AI use.
• Built a device telemetry pipeline for wearable health data ("Qpulse") ingesting raw device signal streams and running anomaly detection; direct exposure to device telemetry signal analysis.
• Built a practitioner verification pipeline integrating five external Kenyan medical registries with confidence-weighted scoring required reconciling inconsistent upstream data sources into one trustworthy output.
• Authored architecture documentation for the platform so pipeline and system logic could be understood and extended by others, not just the original author.

Data Infrastructure Engineer - E&M Technology House

• Worked on core-banking data infrastructure serving 300+ SACCOs across Kenya and Uganda a multi-country environment where reporting accuracy and traceability directly affected member-facing financial decisions.
• Wrote and owned SQL queries and reports used for SACCO reporting and operational decision-making, delivered via an automated email reporting pipeline to stakeholders.
• Built dashboards in Power BI for SACCO stakeholders, loaded into a web app built with Angular, giving stakeholders self-serve visibility into their own data.
• Documented data logic and dependencies so queries and reports could be understood and maintained by others, not just the original author.
• Collaborated cross-team via Microsoft Teams and maintained reporting documentation in SharePoint.

Data Engineering Bootcamp - LuxDevHQ

• Completed an intensive data engineering program covering the modern batch and streaming stack: Airflow for orchestration, Spark for processing, Kafka and Debezium for change-data-capture and streaming ingestion, and dbt for transformation.
• Built and debugged an end-to-end e-commerce data pipeline (Airflow, Spark, Kafka, dbt, Cassandra, Debezium) from raw ingestion through to modelled, query-ready tables.

BSc - Software Engineering - Kirinyaga University

Data Engineering Bootcamp - LuxDevHQ