01 A little introduction
Rujikorn Ngoensaard
Senior Data Engineer
I build and operate
enterprise data platforms.
Where I started
Bachelor’s in Electrical and Electronic Engineering,
Ubon Ratchathani University, 2013–2017.
Outside of work
02 The journey
An evolving practice across manufacturing, commerce and enterprise data.
2013–2017 · The foundation
Electrical and Electronic Engineering
Ubon Ratchathani University
Nov 2017–May 2020
Process Engineer, Engineer I
Developed diagnostic and repair-routing automation for HDD testing. Operated scripts across 130+ Linux VMs and coordinated technical repair and retest work.
May 2020–Dec 2021
Product Design Engineer
Promoted from Senior to Staff Engineer
Automated reporting and centralized data workflows with Airflow. Redesigned ML prediction services for HDD testers.
Jan 2022–Jan 2023
Data Engineer
Built personalization pipelines, search and product-discovery services. Selected website placements recorded more than 50% relative improvement in click-through rate.
Feb 2023–Jul 2024
Data Engineering Specialist
Delivered AWS lakehouse pipelines for 150+ sources within assigned domains. Built governance foundations and enabled experiment tracking through a private MLflow deployment.
Oct 2024–Present
Senior Data Engineer
Build and operate enterprise data platforms across integration, analytics, governance and production support. Lead technical delivery with three outsourced engineers and design target architecture with infrastructure and security stakeholders.
03 Selected work
Senior Data Engineer
October 2024–Present
I build and operate enterprise data platforms and lead technical delivery with three outsourced engineers.
Azure · Databricks · Microsoft Fabric
Led Tableau-to-Fabric data-engineering delivery despite undocumented lineage and dependency constraints.
Automated daily access processing while preserving business-owned decisions. Live since July 2026.
Translated platform assessment into architecture and operating-model decisions. Direction approved; preparation continues.
Build and validate ingestion from SAP, Salesforce, databases and APIs using ADF, Databricks and ADLS.
Developed naming, metadata, ownership and access standards; adoption remains in progress.
Investigate Fabric throttling and self-hosted integration runtime (SHIR) bandwidth to guide capacity and scheduling decisions; coordinate incidents and vendor follow-up.
Analytics Migration Central Pattana
Delivered project scope:
Move Tableau analytics and supporting datasets to Microsoft Fabric and Power BI.
Data dictionaries, business specifications and clear source ownership were missing; direct source access was restricted, making dashboard-to-source dependencies difficult to establish.
I led technical delivery for the data-engineering work, including lineage reconstruction, ingestion coordination and validation.
Direct source-database access was restricted for this migration. Source delivery used data files plus accompanying metadata files for file-level validation.
Source delivery
ADF
Zero records Skip
Skip all remaining downstream tasks for that batch.
Nonempty batch Databricks
Check row counts and columns against the accompanying metadata.
Power BI results must match the equivalent Tableau report for the same reporting period.
RLS Automation Central Pattana
Scheduled daily processing replaced manual refresh, extraction and macro execution, generating 12 domain workbooks. Live since July 2026.
Make daily access-data processing and distribution repeatable while preserving established business rules and downstream contracts.
Organisational changes and unresolved assignments still required business decisions; automation had to preserve legacy-compatible outputs.
Engineering owner for the master RLS pipeline and dashboard distribution.
Organisation data + prior approvals
Scheduled ADF/Databricks processing
Workbooks + Fabric datasets
Next scheduled run
Business review
New groups
Business decisions
Reviewed assignments
Daily processing continues while reviews are outstanding.
Workbook contracts preserve approved sheet structures, headers, column order, required blanks, dashboard mappings and all 13 regular-user access attributes.
Special users retain approved exception assignments and values without inheriting regular organisation-group assignments or recalculating those attributes. They are appended without deduplicating by email.
Processing generates fresh workbooks and configured Fabric datasets. Workbook generation does not run VBA or require existing macro-enabled files.
Current organisation data identifies who exists; business reviewers own access decisions. Regular users can inherit their existing organisation group’s approved assignment.
No.A reviewed No is a decision; blank is not approval. New groups enter the review queue with blank review fields and effective access of No while unresolved.
Existing business decisions are imported before rebuilding the queue. Completed assignments are applied, unresolved items retained and resolved items removed from the next queue. Later decisions feed a subsequent run.
Checks cover source structure, row counts, protected joins, assignments and output schemas. Run-linked logs connect processing and distribution. Source, permission, processing and publishing errors surface as explicit failures; publishing handles locked SharePoint files.
Configured PII is encrypted before persistence in Databricks data; protected matching uses deterministic hashes. Azure Key Vault protects encryption material, with separate DEV/PRD keys and security configurations.
Authorised exports decrypt required PII. Excel outputs and configured Fabric destinations may contain decrypted information; logs exclude plaintext employee data and secrets.
Azure Target Architecture Central Pattana
Target direction approved; transition preparation is in progress. Publication method and validation of proposed controls remain open.
Clarify ownership, access, publication and operational responsibilities while retaining working platform controls.
Ownership, access, publication and operating responsibilities span CPN Azure and RIS Fabric, requiring clear boundaries and handoffs.
I assessed the platform and designed the target with infrastructure and security stakeholders, aligning responsibilities and transition priorities.
CPN Azure / RIS Fabric
Public paths
Daily Databricks-to-OneLake copies
RIS foundation / CPN workloads
Private paths / Approved destinations
Publication undecided
Separate approvals
Existing: Unity Catalog, DEV/PRD. Fabric access stays separate.
Proposed: recovery objectives, restoration tests, release approval, tested rollback.
Solid: current. Dashed: proposed.
The platform assessment shaped four design themes and transition priorities with infrastructure and security stakeholders.
| Assessment theme | Finding → proposed response |
|---|---|
| Ownership and access | Responsibilities are undocumented and catalog owners unassigned. I proposed accountable data ownership, recorded approvals, periodic reviews and time-limited access. |
| Controlled connectivity | Partial network restrictions informed private service paths, shared network responsibilities and approved outbound destinations, distinguishing browser access from data transfer. |
| Trusted publication | Daily copies lack ownership and validation. The response pairs publication ownership and consumer approval with freshness checks and source-to-copy reconciliation. |
| Operational readiness | Alerts and artifact promotion already work. Missing recovery and release safeguards call for agreed recovery objectives, restoration testing, release approval and tested rollback. |
Retain Unity Catalog-governed ADLS access, DEV/PRD separation, centralized secrets, production failure alerts, cost controls and unchanged DEV-tested artifact promotion. Preserve existing account-removal and integration practices. Fabric access requires separate approval.
Team Head approved the target direction; individual standards require separate approval. Proposed responsibilities place identity and shared foundation with RIS, delegated platform workloads with CPN, and accountability with domain workspace and catalog owners.
The future publication method and connectivity remain open. Transition preparation continues; migration, recovery readiness, control closure and measured risk reduction remain incomplete. Data restoration and release rollback require separate validation.