Applied AI systems & data engineering
I’m Tera Earlywine. I design agent-enabled tools and the data infrastructure behind them, with clear state, human controls, and evidence of what happened. My background spans data platforms, compliance workflows, and AI-assisted application development.
Subtract posted refunds from completed sales.
Migration programs I’ve worked on spanned
500+ workflowsMy optimization work identified
$500K+ in projected Snowflake savingsSelected work
Staging proof of concept
For a client, I designed an audit-agent proof of concept around clear workflow steps and reviewable context. I documented the gaps and handoff; this was a proof of concept, not a production deployment.
Read the case studyIndependent project · Active development
A platform for provisioning and deploying web applications with GCP, Terraform, GitHub, and Firebase. I own the architecture, requirements, direction, review, and troubleshooting, with AI-assisted implementation. The project is in active development, not a claim of customer adoption or production scale.
Discuss the architecturePrior work · Platform engineering
I’ve contributed to migration programs spanning 500+ workflows. My infrastructure optimization work identified $500K+ in projected Snowflake savings.
Data platform modernizationPrior roles · Block & Mercari
At Block, I helped set technical direction as a staff data engineer. At Mercari, I worked across business intelligence, warehouse engineering, and data engineering.
See my experienceIllustrative data example
Two sales total $600. Post a $40 refund and follow the number from the source records to the reconciliation check.
$600 − $40 = $560
Both sales are complete. The posted refund reduces net sales by $40.
Use the refund’s posting date and count each refund ID once. Both sales and the optional refund post in the same reporting period here. Reconcile the result to the ledger for that period.
Services
Start with one warehouse and an agreed set of workloads. The paid Data Waste & Efficiency Diagnostic gives you a baseline, ranked improvements, and a way to measure the result.
Explore the diagnosticTrace one failing workflow from source to report. Your team gets a dependency map, reconciliation checks, and clear criteria for the next cutover or rollback.
Plan a migrationEvaluate one workflow for accuracy, access, cost, and escalation. Bring an evaluation report, release criteria, and an operating runbook to the review.
Explore applied AI workflowsTera's approach
Start with a defined decision and agree on scope, responsibilities, and acceptance criteria. Each stage produces the evidence and operating context needed for the next.
Find the failure modes, hidden dependencies, and actual business cost.
Choose the smallest architecture and operating model that resolves the risk.
Ship a production-shaped slice and measure it against reality.
Extend the pattern with clear controls, ownership, and adoption.
Leave behind a system your team can understand, run, and improve.
Ongoing data and AI reliability support can cover incident follow-through, runbooks, control evidence, and a prioritized improvement backlog. Scope and service expectations are agreed for each engagement.
About & experience
I build applied AI systems on a foundation of 9+ years across fintech, marketplaces, consulting, analytics, and data-platform engineering. I’m exploring AI Engineering and Applied AI Engineering roles, as well as senior data and AI consulting roles or contracts.
Tera Earlywine Consulting
I advise engineering teams on platform reliability, modernization, compliance workflows, and applied AI.
Block.xyz
I built and scaled financial data infrastructure and helped set technical direction across platform work.
Block.xyz
Mercari
Mercari
This is Alice
Mercari
Mercari
I developed my foundation in SQL, data modeling, and analytics.
Straight answers
Tera Earlywine is an independent data and AI consultant with 9+ years of experience building and modernizing enterprise data platforms across fintech, marketplaces, and regulated operations.
She helps engineering teams stabilize data platforms, rescue migrations, build AI-ready data foundations, and design agent workflows with explicit state, human controls, and operational evidence.
Tera works with startup founders, growing data teams, and enterprise platform and risk leaders across fintech, B2B software, and marketplaces.
Bring Tera in when a critical data platform is fragile, a migration is stalled, ownership is unclear, or an AI pilot needs the controls and infrastructure required for production.
It starts with a 20–30 minute fit call. If the problem is a match, the first engagement usually diagnoses the risk, defines the smallest useful path, and produces a concrete next decision.
Speak with Tera
Tell me what your team is trying to fix. A 20–30 minute fit call gives us time to talk through the problem and agree on a useful next step.