Matthew Porter

About Matthew Porter

I publish deep-dive articles on AWS & GCP scalable data analytics topics: https://medium.com/@matt.porter_76759At Natera, I am bridging the data gap between clinical and genomic data in production clinical software. Leading a Redshift-to-Snowflake migration powered by dbt and Terraform Cloud, designing and deploying RAG-powered AI tooling using AWS Bedrock Knowledge Bases, and delivering multiple greenfield production applications under extremely aggressive timelines with recognition up through the C-suite. Claude Code native: I presented \"You\'re the Architect: Using Claude Code Effectively\" to ~600 employees at Natera\'s Gen AI conference hosted by AWS. Drove $308K/yr in realized AWS cost savings with $513K/yr pending, and authored a proposal targeting $1.9M-$3.8M/yr in automated savings across 29 AWS accounts.At DoiT International, I designed and debugged cloud architectures for hundreds of companies looking to grow their data operations, with an emphasis on the genomics and healthcare industries. I ran a pod of senior cloud architects (>98.5% CSAT over several years) and guided the growth of the CRE practice as the company rapidly scaled. In 2024, I built three LLM-powered tools solving complex departmental issues, one of which caught the CEO\'s attention and won an internal tech challenge. I also led a team that created a clinical genomics app for the AWS Gen AI Partner Competition, going from PoC to deployed on the AWS marketplace in 6 weeks.Prior to DoiT, I engineered AWS solutions with security clearance for government clients at Effectual.At GenomeNext, I led a team developing automated bioinformatic analysis and annotation solutions at scale on AWS. As Director of Bioinformatics, I designed high-throughput workflows yielding clinically relevant results and multi-million dollar follow-up studies for cancers including bladder, prostate, chordoma, and melanoma, as well as pulmonary arterial hypertension.Prior to GenomeNext, I worked as a bioinformatics scientist at Bayer CropScience, designing automated bioinformatics tools and workflows for variant retrieval, filtering, and RNA-Seq analysis.

Experience

1. Staff Data Architect, Clinicogenomics

   Natera

   Mar 2025 — Present · Eugene, OR, US

   Bridging the data gap between clinical and genomic data in production clinical software.Leading a Redshift-to-Snowflake migration powered by dbt and Terraform Cloud, establishing a scalable, cost-effective DWH foundation for clinical data, AI, and GenAI workloads. This has included reconciling ~620 DDL entities across sbx, qa, and prod environments, with all pipelines and applications documented and migration orchestrated.Claude Code native. Presented \"You\'re the Architect: Using Claude Code Effectively\" to ~600 employees at Natera\'s Gen AI conference hosted by AWS (Feb 2026), demonstrating via A/B test that AI coding tools only produce scalable systems with deliberate architectural guidance. The guided approach ran ~250K jobs in <24h at 70% of the cost, while the unguided approach exhausted quotas, saw cascading job failures, and overwhelmed Redshift.Drove $308K/yr in realized AWS cost savings with $513K/yr pending through systematic audits. Built governance infrastructure cataloging a 2.35 PB production footprint at <$70/mo. Authored a proposal to automate cost optimization across Natera\'s 29 highest-spend accounts, targeting $1.9M-$3.8M/yr in savings.Built a BAM de-identification pipeline from scratch on AWS Batch with Graviton4, reducing weeks of sequential work to <1 hour parallelized at ~90% lower per-job cost.Designed and deployed RAG-powered production tooling using AWS Bedrock Knowledge Bases, vector databases, and a Lambda-backed API Gateway, facilitating hundreds of clinical conversations with citation-backed responses.Created dozens of Snowflake semantic views and delivered a C-suite Gen AI demo with Snowflake Intelligence Agent.Automated analytical pipelines via AWS Batch (~200K parallel jobs on spot instances), meeting urgent delivery deadlines.Developed Airflow DAG monitoring with 99th percentile runtime anomaly detection. All infra built with Terraform, deployed through dev/preprod/prod in Terraform Cloud.

Education

• University of Florida

  Bachelor of Science (BS), Chemistry with a Focus in Biochemistry

  2006 — 2010

• University of California, Davis

  Master of Science (MS), Integrated Genetics and Genomics

  2010 — 2013

Skills

• Data Visualization
• Molecular Biology
• Amazon S3
• Hidden Markov Models
• Python
• Amazon Sqs
• Amazon Rds
• Apache Spark
• Amazon Emr
• Molecular Genetics
• Data Science
• Big Data
• Git
• Biochemistry
• Sql
• Rnaseq
• Ngs
• Amazon Ec2
• Sequence Analysis
• Data Analysis
• Genetics
• C++
• R
• Bioinformatics
• Computational Biology
• Amazon Web Services (Aws)
• Genomics