Mufaddal Naguthanawala

MasterControl · Salt Lake City, UT · January 2026 – Present

Provisioned AWS MWAA (Managed Airflow) environments across dev, stage, and production in multiple regions using Terraform, codifying VPC networking (subnets, route tables, security groups) and IAM policies to enable secure, highly available data orchestration across 30+ pipelines.
Scripted Airflow DAGs in Python to orchestrate dbt transformations and ML pipelines, managing cross-system dependencies across Snowflake and AWS to replace manual workflows and reduce operational runtime by 50%.
Implemented multi-environment CI/CD pipelines in GitHub Actions to automatically sync DAG code to MWAA S3 buckets, reducing deployment cycles from 1+ hour of manual work to under 20 seconds.
Established end-to-end observability for MWAA environments using CloudWatch metrics, custom alerts, and Grafana dashboards to track DAG health, task latency, and worker utilization, reducing incident response time by 80%.

Exact Sciences · San Diego, CA · May 2025 – August 2025

Migrated bioinformatics pipelines from an on-premises SLURM HPC cluster to AWS HealthOmics using a serverless microservices architecture (Lambda, EventBridge, DynamoDB) that delivered QC metrics to external review systems, reducing infrastructure costs by 30%.
Engineered idempotent Kafka producers with retry logic and dead-letter handling to guarantee at-least-once delivery, processing 15,000 events/day at 99.9% success rate.
Partnered with bioinformaticians and platform engineers to translate scientific QC requirements into system specifications, and authored technical documentation and runbooks that enabled the team to operate and extend the orchestration layer independently.

Gyori Lab for Computational Biomedicine · Boston, MA · September 2024 – April 2025

Evaluated and labeled scientific literature surfaced by an ML relevance-ranking model for the Bioregistry project, generating training data that fed back into model fine-tuning to improve classification performance over successive iterations.
Wrote unit tests with Pytest to validate training data integrity before model ingestion and integrated them into the project's GitHub Actions CI pipeline, catching schema and data quality issues before they affected model performance.
Presented research on ML-driven biocuration at the 2025 Biocuration Conference, showcasing system design for scalable literature classification.

UW Medical Center · Seattle, WA · August 2022 – June 2024

Self-taught Python and web development to build a Flask application that automated lab quality control reporting, reducing turnaround time by 2 days and replacing paper-based workflows for the lab team.
Processed patient samples using NGS platforms (Illumina) and reported diagnostic results in a high-volume clinical lab, contributing to lab operations while transitioning into software engineering through self-directed projects.

Overview