Dennis Rowe — Lead Platform Engineer · Omega Point

Dennis Rowe — Lead Platform Engineer · Omega Point · Austin, Texas Metropolitan Area.

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About

4x early startup employee. 2 successful acquisitions. 20+ years of software development and infrastructure experience.

I thrive in the high-growth chaos of early-stage startups. From my first startup (Involver → Oracle) to my current role at Omega Point, I've been the engineer who joins early, builds the foundational systems, and scales them through hypergrowth and acquisition.

What I've Built: At Omega Point, I designed and implemented the entire data pipeline infrastructure—Airflow, Databricks, data lake—that processes all partner and customer financial data. I'm also actively supporting AI adoption across the organization, both in production systems and for developer productivity.

Startup Track Record: • Omega Point (current) – Fintech startup, Lead Platform Engineer • Apcera → Ericsson acquisition – Container platform, Senior SRE • WP Engine – WordPress hosting, core engineer on HA platform • Involver → Oracle acquisition – Social marketing, DevOps

I also spent time at Dell MessageOne building monitoring systems in Clojure, and at Cirrus Logic introducing DevOps practices. I specialize in cloud infrastructure (AWS, Azure, GCP), data engineering, security implementation, and building DevOps cultures from scratch. I've deployed and supported platforms for Fortune 50 companies while keeping the scrappy startup mentality.

Experience

Lead Platform EngineerCurrent
Omega Point · Austin, Texas Metropolitan Area
Apr 2019 – Present
Built the firm's first in-house equity factor risk models — US, then worldwide — from spike to production, retiring the vendor model they replaced. Full medallion stack on Databricks/Spark: universe construction, factor regression, risk/exposure calculation, export. • Solved non-synchronous market bias (Dimson beta) for a global universe regressing onto US-listed factors, and globalized a US-only sector classification that broke silently on international schemes. • Shipped model validation as a reusable tested battery — coverage/correlation vs incumbent vendor models, failing the run on any breach — instead of one-off notebooks. • Onboarded and maintained 30+ vendor risk models (Barra, Axioma, Wolfe) across US, European, Asia-Pacific, China, Canada, EM, small-cap and climate mandates — each spanning four repos plus multi-hour history backfills to 2015. • Built a generalized ingestion framework for a major financial data vendor, adding fundamentals, estimates, ratios and corporate-events content sets on a common base class. • Led the Airflow 2 → 3 upgrade of the primary data-engineering deployment. • Killed recurring DAG timeouts and driver OOMs by vectorizing the ETF exploder, fixing a silver pipeline that forward-filled full history before its date filter, and scaling the global build out on Spark. • Eliminated stale-build bugs by pinning Databricks jobs to immutable image digests; hardened concurrent Delta writes with conflict retry; added OpenTelemetry tracing to the market-data service. • Rebuilt internal monitoring into a model-delivery/SLA system with escalation and auto-resolving alerts, plus automated daily anomaly scans that separate real signal from baseline noise. • Built an orchestrator for parallel AI coding agents in isolated git worktrees (one per ticket), a Databricks ops CLI/TUI, and an ADR-backed agentic workflow library — adopted by the team, replacing commercial tools under evaluation.