About / Charnrit Khongthanarat
The experiences behind my current build
Analytics Engineer — external consultant at Pandora
May 2026 - Present
I connect business needs with data preparation, semantic models, and reporting. I design solutions, make technical trade-offs, and coordinate delivery, validation, and ongoing changes.
At Pandora, I create new datasets and reports while maintaining or enhancing approximately 20 datasets/reports combined.
Engineering responsibility, in practice
At Accenture, I owned the Power BI reporting workstream on a trading analytics assignment. This covered reporting design, semantic models, DAX, test cases, source-output validation, and coordination with business users, technical teams, and the vendor.
Colleague feedback across project contexts highlights this scope:
- Project Lead S.S.
- Highlighted reporting-design ownership across data extraction, processing, and Power BI, alongside data-lifecycle understanding, stakeholder communication, and support across workstreams.
- Senior Manager Y.L.
- Described bridging backend data engineering and reporting through modeling, ETL, requirement translation, and technical discussions.
- Account Lead N.C.
- Described technical architecture leadership for a particular POC and communication with senior IT clients.
The motivation to automate
I worked across commercial outreach, content, training/coaching support, and partner development in a people-development consultancy. Repeated Excel reporting and customization for assessment-related work sparked my interest in automation and reusable systems.
Delivering and maintaining a complete solution
At BCSC, I delivered a custom sales-incentive solution for an anonymized luxury-watch retailer. My scope covered requirements, data preparation, calculation logic, reporting, training, maintenance, and enhancement. The work progressed from historical Excel reporting and standardized inputs to transaction-based calculations incorporating campaign rules, eligibility changes, and manual adjustments.
A design trade-off
I initially separated historical and newly calculated information because it seemed easier to validate. Later changes exposed difficulties with DAX, relationships, naming, and reconciliation. I made targeted repairs and selectively redesigned areas when effort and wider impact justified it.
A solution needs room for future change. Maintenance responsibility reveals the consequences of design decisions.
Learning enterprise practice
Through migration and POC work, guidance from a Practice Lead, and participation in an enterprise rollout, I learned practices I later reused: naming conventions, report templates, and performance tracking and tuning.
I also conducted internal training on connecting interactive Power BI reports to paginated reports through dynamic links and prefilled parameters.
Read the Cognos-to-Power BI migration caseBroader technical ownership
My responsibilities spanned data preparation and modeling, reporting design, validation, performance work, stakeholder and vendor coordination, and technical guidance.
On a retail analytics modernization project, I redesigned the reporting layer into subject-specific models and pre-aggregated tables, ran concurrency tests, and coordinated infrastructure tuning with platform colleagues.
Other assignments involved stakeholder refinement, documentation, and handover. Data-quality reporting also required refresh coordination and delivery within a secure environment.
Read the reporting-layer modernization caseBuilding and sustaining reporting
My ongoing responsibility combines new reporting development with changes to existing reporting. I use PBIP/Git, reusable components, agent-assisted investigation, and checks around changes to make that work more reviewable.
Agents also help compare dataset states and prepare structured findings about data-quality issues and mapping gaps for my own review or discussion with business analysts and data engineers.
How I work
I direct Codex and other agents to investigate context, co-design approaches, implement changes, and review results. I remain responsible for the decisions and validation.
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Clarify the business decision and data context
Understand what stakeholders need, where the data comes from, and which definitions require agreement. Agents support investigation and comparison.
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Connect data design with the reporting experience
Work across preparation, semantic models, and report behavior. I co-design approaches with agents and direct implementation within the project's constraints.
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Make changes reviewable and validate their effects
Review and refine contributions, compare outputs with source information, and distinguish completed checks from unresolved questions.
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Help colleagues understand, use, and maintain the work
Share reusable patterns and structured findings for review, training, and handover.
Where I'm heading
I'm working toward broader solution ownership in forward-deployed engineering and solution or data architecture. I want to stay close to business problems while taking greater responsibility for technical design, delivery, and helping people use the results.
Preparing to teach Databricks courses; onboarding and required qualifications remain in progress. Alongside that, I'm exploring recurring problems worth solving through a product that can scale.
I learn through experimentation, listen to AI-engineering podcasts during my commute, and share useful approaches with colleagues.