Modern data platform design, engineering and delivery — from enterprise data warehouses and lakehouse architecture through to self-service analytics and executive reporting.
AIONIX has designed and built data platforms across some of the APAC region's largest organisations — including national broadband infrastructure, healthcare analytics platforms, manufacturing data warehouses and financial data platforms for major banks in the APAC region. Our data engineering practice combines architectural rigour with production delivery experience.
We work across the full data stack: ingestion, transformation, modelling, governance and consumption. Our platforms are built on modern tooling — Snowflake, Databricks, Microsoft Fabric, dbt, Azure Data Factory, AWS Glue — and engineered for the scale, reliability and security that regulated enterprises require.
Lakehouse, warehouse or hybrid — we design the right architecture for your data volumes, latency requirements, team capability and budget.
Pipeline engineering, data modelling, transformation layer design and testing frameworks. Built for reliability, observability and maintainability.
Data cataloguing, lineage tracking, data quality rules, ownership frameworks and regulatory metadata management across enterprise data estates.
Self-service analytics layer, executive dashboards, KPI frameworks and governed semantic models on Power BI, Tableau and QuickSight.
Structured migration programmes with reconciliation frameworks, bronze/silver/gold validation and zero-loss cutover management for complex data moves.
Event-driven data architectures, Kafka pipelines, Spark Streaming and real-time operational dashboards for latency-sensitive business processes.
Talk to our data engineering team about your current stack, your pain points and what a modern platform would unlock.