Pysynapse

Resume

Kris Kokomoor

Principal Data, Platform & Systems Engineer

Cloud architecture, Embedded Systems (IoT), and AI-augmented engineering leadership

Engagement Models

Permanent leadership (Principal/Director), fractional head of data, and strategic consulting for regulated industries.

Typical Problems Solved

High-stakes reporting trust, agentic pipeline management, audit-ready cloud architecture, and edge-to-cloud IoT integration.

Common Stacks

Python, C++, SQL, Airflow, dbt, BigQuery, Kafka, OpenClaw, Terraform, AWS, GCP, ESP32, Docker, Prometheus.

Professional Summary

Experienced engineering leader specializing in cloud-native data platforms, IoT systems, and AI-augmented engineering. Proven track record in **healthcare and regulated environments** where traceability, audit-readiness, and reliability are paramount. Combines deep systems-level expertise (C++, Linux, performance engineering) with modern cloud and agentic AI tooling to deliver transparent, cost-aware solutions for high-stakes data flows.

Core Skills

  • Data Platforms: BigQuery, PostgreSQL, dbt, Airflow, Kafka, Snowflake, DICOM/PACS
  • Cloud & Infrastructure: GCP, AWS, Cloud Functions (Gen2), Cloud Run, Terraform, Pulumi, Docker
  • Embedded & IoT: ESP32, C++, sensor integration, real-time telemetry, memory-constrained optimization
  • AI & Agentic Systems: Agentic dbt/BigQuery management, LLM-driven diagnostics, OpenClaw workflows
  • Quality & Reliability: GXP compliance, audit trails, schema drift detection, observability, validation frameworks
  • Systems Engineering: Linux/UNIX, networking, performance tuning, distributed systems architecture

Experience

Podimetrics | Principal Quality Engineer, Data & Platform Engineering (2024-2025)

  • Designed and implemented a quality-first data platform for patient-facing analytics in a regulated (GXP) healthcare environment.
  • Built Airflow-orchestrated pipelines integrating Cloud Functions (Gen2), BigQuery, and dbt with a focus on audit-readiness and reliability.
  • Explored LLM-assisted validation and anomaly detection to accelerate triage in high-stakes clinical data pipelines.
  • Architected and deployed a production Airflow environment on GCP using infrastructure-as-code (Pulumi) and PostgreSQL metadata.

Recent Exploration — IoT & Agentic AI Systems

  • Embedded Systems (Irrigation): Built a full-stack IoT solution using ESP32 (C++), bridging real-time hardware sensors with a Python/Docker cloud API for automated telemetry.
  • Agentic Data Engineering: Integrating LLMs into engineering workflows (OpenClaw) for automated dbt model generation and pipeline diagnostics.
  • Full-Stack Data Lifecycle: Demonstrating "silicon-to-cloud" capability, from physical actuation to high-level analytics and governed reporting.

SURL | Founder and Principal Engineer (2023-2024)

  • Designed and built a secure, auditable data transfer platform for regulated datasets using Kafka, PostgreSQL, and Python on AWS.
  • Implemented explicit ingress and egress cost tracking to support cost-aware decision-making in cloud-native environments.

Pfizer | Senior Engineering and Data Leadership Roles (2009-2023)

  • Led large-scale clinical data and image metadata processing initiatives in high-stakes regulated environments using AWS, Spark, and Snowflake.
  • Designed search capabilities for clinical image archives spanning DICOM attributes and trial parameters to improve research access.
  • Driven global modernization of clinical and analytical platforms supporting regulated research and reporting.

Early Career | Systems and Infrastructure Engineering (1986-2009)

  • Built foundations in UNIX, Linux, and performance engineering that inform current cloud and embedded systems work.

Education

  • B.S. Mathematics, University of Florida
  • M.S. Electrical Engineering, University of Florida
  • M.B.A., University of Rhode Island
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