Opportunity value
SUM(amount_usd) for all records within the selected region and period. One row per opportunity is the intended grain.
Senior Solutions Engineer · Singapore
Good data.
Clear stories.
Decisions that move.
I’m Rex Piloton. I connect software engineering, data quality and enterprise presales to help customers see what’s possible—and prove why it matters.
SQL Server + Oracle → Experian data management → Enterprise AI & presales
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1 → 5APAC SE team growthEverbridge · team contribution
+8%Deal closure improvementEverbridge · Project Uplift contribution
SQL + OracleDatabase development foundationMicrosoft enterprise developer credential
Data qualityManagement & trusted dataExperian · Southeast Asia
01 / A working point of view
A number is only as good
as its definition.
Explore a small analytics workbook. Filter the region, inspect the logic, then introduce duplicate records. See how a data quality issue changes the story.
Opportunity value · USD—
Won value · USD—
Win rate · closed opportunities—
Won value by month · USD
Opportunity value by region · USD
Won value
SUM(amount_usd) where status = 'Won'. Amounts are illustrative USD contract values, not recognised revenue.
Win rate
Won opportunity count ÷ (Won + Lost opportunity count). Open opportunities are excluded. Counts use the displayed rows so duplication remains visible.
A governed metric needs a definition, a grain, filters and a source. A consistent calculation alone cannot repair duplicated source records.
SQL shown mirrors the selected workbook filters and duplicate scenario. The browser calculates the demo from the same sample rows; it does not connect to a warehouse or execute this SQL.
| Opportunity ID | Month | Region | Status | Amount · USD |
|---|
Built by Rex as an application demonstration. Independent implementation; not an Omni product embed. All opportunity data is synthetic.
02 / Why this background matters
From data foundations
to customer conviction.
The thread through my career
Trust the data.
Understand the decision.
Prove the outcome.
At Experian, my work centred on data management and data quality. In enterprise presales, the same discipline applies: understand the inputs, agree on what success means, and make the evidence clear enough to act on.
Source→Validate→Define→Demonstrate
Software development foundation
Microsoft Certified Professional Developer — Enterprise Applications
Technical depth with a business lens.
SQL Server and Oracle experience, backend development, APIs and integrations. I can move between implementation detail and the customer outcome it needs to support.
Evaluations that help buyers decide.
Discovery, tailored demos and POCs across Ada, Everbridge, Zendesk and Kasisto. Define the decision criteria, make the use case tangible, and explain the path to implementation.
Regional ownership, with team impact.
Founding APAC presales at Ada. Helped grow Everbridge’s APAC SE team from one to five. Built regional capability at Experian and Kasisto.
03 / Career evidence
Different platforms.
The same customer discipline.
Ada · Current
Founding APAC presales
Technical discovery, tailored AI demonstrations, architecture discussions and POCs. Connect CX goals with integrations, evaluation criteria and business value.
Regional ownership + hands-on proof building
Everbridge
Principal Pre-Sales Engineer, APAC
Enterprise evaluations, integrations and executive presentations. Supported the largest APAC CEM Suite deal.
Team 1 → 5 · Project Uplift: +8% deal closure contribution
Experian
Data management & quality
Head of Pre Sales and Technical Services, Southeast Asia. Technical requirements, implementations, executive alignment and regional team development.
Trusted data + regional technical leadership
Kasisto
Director of Sales Engineering, APAC
Conversational AI technical sales for financial institutions. Demos, pilots, integration planning, deployment scoping and value narratives.
Complex enterprise buyers + team building
Zendesk
Enterprise solutions consulting
Advised business and IT leaders across APAC on service workflows, APIs and CX transformation. Built reusable demos and enablement.
Consultative discovery + platform storytelling
Engineering foundation
Build it. Explain it. Prove it.
Enterprise application development with SQL Server and Oracle. Microsoft Certified Professional Developer — Enterprise Applications.
Backend foundations that support technical credibility
04 / Recent hands-on work
Make the evidence
part of the experience.
My Pacifica Airways demonstration connected a multilingual voice agent to booking tools, seat maps and a live customer journey. Its readiness dashboard made tool accuracy, confirmation controls and failure behaviour inspectable.
How I would approach an Omni evaluation
Start with one question
the customer cares about.
Agree on the metric and success criteria. Inspect the source data and access constraints. Build the smallest credible proof. Let stakeholders explore, challenge and validate the result.
This is my proposed evaluation approach, not a claim of prior Omni implementation experience.
05 / A note to the Omni team
Help customers get from
“interesting” to “we trust this.”
Omni’s focus on trusted answers connects with a theme running through my career: technology creates value when people can confidently use it to make a decision.
I bring a software engineering foundation in SQL Server and Oracle, data management and data quality experience at Experian, and enterprise presales experience across APAC. I’ve built demonstrations, led technical evaluations, worked with executives and practitioners, and helped teams grow.
I would bring that combination to Omni: curiosity about the customer’s data, discipline in proving the use case, and a clear story about why the result matters. I’m keen to deepen my experience with Omni and the modern analytics stack while contributing the enterprise and regional experience I already have.
Rex Joseph Piloton
Singapore · Singapore Permanent Resident
Next query
Let’s explore the fit.
I’d welcome a conversation about building Omni’s customer impact in APAC.