EVE JOHNS
01

About

I work in data and product systems, with a focus on operational clarity, reliability, and how complex systems behave in real-world environments. My work has spanned analytics, data engineering, and technical leadership, often at the intersection of engineering, product thinking, and organizational decision-making.

I hold a master's degree in Statistics, following a bachelor's degree in Business Administration. I then found my way into tech through software development and data science projects. Over time, I moved from individual contributor roles into leadership, shaped by both hands-on technical work and the responsibility of guiding teams through ambiguity and change.

Outside of work, I enjoy gardening, making art, and exploring ideas through technology.

02

Work

A selection of initiatives I've led and supported—focused on operational clarity, reliability, and how systems behave in production.

Reliability & Data Ingestion Systems

Led the evolution of data ingestion foundations to improve reliability, reduce operational noise, and support scale across multiple workflow patterns.

Focus
  • Operational design for systems that hold up in production
  • Clear ownership boundaries and durable interfaces
  • Guardrails that make change safer over time
Impact
  • Fewer repeat incidents and smoother release cycles
  • Faster triage through clearer signals and accountability
  • Reduced manual intervention across recurring workflows
Operational DesignReliabilityTechnical Leadership

Scaling Delivery

Led planning and execution across multiple initiatives, balancing delivery, prioritization, and team capacity while navigating ambiguity and shifting constraints.

Focus
  • Prioritization and roadmap shaping under real-world constraints
  • Unblocking work by clarifying decisions and ownership
  • Clarifying priorities and reducing noise so teams can focus on delivery
Impact
  • More consistent delivery across parallel initiatives
  • Fewer context switches and clearer decision paths
  • A steadier, more sustainable pace for the team
Technical LeadershipDeliveryPrioritization

AI-Augmented Engineering

Exploring AI-assisted approaches to interpreting system behavior, surfacing patterns earlier, and lowering the cognitive effort required to understand complex environments.

Focus
  • Experimenting with AI tools in day-to-day engineering workflows
  • Evaluating where AI meaningfully reduces cognitive loadd
Impact
  • Faster iteration during development and review cycles
  • Reduced overhead when navigating unfamiliar code paths
AI AdoptionDeveloper ToolingSystems Thinking

Additional detail is available upon request.

03

Contact

Email is best. I'm also reachable on LinkedIn.