Engineering Leadership · Cloud · Data · AI

Chris Waddell
Engineering Leader for
Cloud, Data & Business Systems

I lead technical execution across infrastructure, data platforms, delivery, and business-critical systems, combining hands-on technical depth with cross-functional leadership to help organizations scale and improve execution.

Lead priorities across engineering, data, IT, and web systems
Rebuilt ETL pipelines with measurable performance gains
Advise executive leadership on technical strategy
Built & operate MarketMoodz, an AI financial analysis platform
01 · About
Turning technical complexity
into reliable execution.
My work sits at the intersection of engineering leadership, cloud architecture, data systems, and applied AI. In practice, that means aligning teams, modernizing systems, improving delivery, and making sure technical decisions support business goals.
02 · Current Scope
What I Lead
Cross-functional ownership spanning the full technical landscape.
01

Engineering Execution

Sprint planning, prioritization, delivery coordination, and technical direction for development work.

02

Cloud & Platform

AWS architecture, infrastructure decisions, operational reliability, and systems design.

03

Data & ETL

Pipeline modernization, data flow design, observability, and performance improvements.

04

IT & Business Systems

Oversight across internal technology operations, support functions, and business-critical technical tooling.

05

AI & Product Development

Independent design and operation of MarketMoodz, including automation, analysis workflows, and end-to-end product execution.

06

Security & Compliance

Lead SOC2 and data compliance efforts, including establishing compliance frameworks and maintaining them over time.

03 · Selected Impact
Proof of Work
Real outcomes from hands-on engineering leadership.

ETL Modernization

Led a rewrite of core ETL pipelines to improve reliability, simplify operations, and create a stronger foundation for future growth, with measurable gains in performance and operational efficiency.

Problem

Existing AWS Glue-based data pipelines had grown overly complex: too many steps, arbitrary constraints, and long runtimes performing unnecessary actions that drove up costs. Time-based scheduling instead of event-driven execution meant runs frequently overlapped, resulting in unprocessed data and unreliable output.

Approach

Simplified pipelines by eliminating unnecessary steps and replacing them with configuration-based, event-driven, serverless Lambda transforms. This enabled fast, inexpensive processing for relatively simple transforms while making schema additions and changes a matter of configuration rather than code.

Outcome
  • Processing time decreased from up to 10 hours to a couple of minutes
  • Costs cut by 80%
  • New integration deployment dropped from 10 months to 2 weeks

Cross-Functional Technical Leadership

Coordinating delivery across cloud, data, IT, development, and web systems. Planning work, supporting execution, advising leadership, and ensuring technical effort stays aligned with company priorities.

Problem

Small companies and startups can't spend money on many different management FTEs for tech. This leaves business leaders to fend for themselves on technical questions, causing confusion and frustration. Technical workers also have to scope and prioritize their own work without proper oversight, leading to poor planning or distractions from what matters most.

Approach

In a startup, you have to balance your time across all areas. It's important to hire technical workers who can manage themselves to a degree, but also know when to ask questions and seek approvals. That lets me be efficient and intentional with my time while keeping everyone moving forward. Having a wide range of experience across nearly all technical domains means I can answer questions without guessing or investing time in extensive research.

Outcome

Business leaders get the answers they need quickly to keep solving problems. Clients feel more comfortable when someone on the call can answer questions or give feedback in real time. Trust is increased and outcomes are achieved without management bloat.

MarketMoodz

Built an AI-powered financial analysis platform from the ground up, owning product direction, architecture, automation, analysis workflows, and ongoing system improvement end to end.

Problem

I've always been interested in investing. I passed the Series 65 Investment Advisor Exam, though I stuck with engineering rather than advisory work. I had dabbled in AI and ML for forecasting but never fully applied it. I wanted a tool to support my own investment planning, knew that LLMs could process the volume and variety of information involved, and wanted to learn firsthand what it takes to operationalize an AI pipeline.

Approach

I designed a system that ingests data from news, social media, and market data sources, processing it into a standardized form for rating and analysis. It runs 24/7, ingesting data in near real time and posting to Facebook and X. AI summarizes everything into bite-sized, understandable insights. The platform currently watches over 1,400 stocks and makes roughly 15,000 LLM calls per day.

Outcome

Built primarily as a personal tool, MarketMoodz has attracted over 100 users organically. The system continues to evolve. It now delivers a morning email summary before the trading day starts. I've been expanding into marketing to more effectively promote the platform while continuing to improve its effectiveness and usability.

04 · Leadership
How I Lead
My leadership style is grounded in clarity, ownership, and execution. I'm most effective in environments where teams need structure, stronger technical alignment, and leadership that can operate across multiple domains. Everyone solves problems in different ways, and I enjoy digging into the "why" with them.
05 · Differentiation
Why My Background Is Different

Many leaders come up through either software delivery, infrastructure, or business systems. My experience spans all three.

Cloud operations, data engineering, delivery planning, internal technical operations, marketing and web systems, and AI product development, all under one roof.

That breadth lets me bridge gaps between teams that are often managed separately but need to work together to deliver results. It's especially valuable in growing companies, reorganizations, and environments where execution needs stronger ownership.

Let's Talk
Let's Connect
I'm open to discussions around engineering leadership, platform strategy, cloud and data architecture, and technical operations.
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