Data engineering that delivers trusted data at scale.
ScaleCloud builds data engineering — pipelines, lakes, transformations, and streaming — so data flows reliably, governed, and ready for analytics, BI, and AI at enterprise scale.
Data flows.
18ms streaming.
Quality & lineage.
4PB managed.
Full-lifecycle data engineering expertise
From ingest to serve — select a stage to see the focus areas, deliverables, and tooling we bring.
Ingest
4PBIngest data from sources — batch, CDC, streaming, and APIs.
- Batch
- CDC
- Streaming
- Ingestion
- Connectors
- Schemas
Ten services across the data engineering lifecycle
A complete data engineering practice — select a service to explore the outcomes and where it fits.
Data Ingestion
Ingest data from sources — batch, CDC, streaming, APIs.
4PBDepth across every data engineering domain
We deliver across the full data engineering portfolio — select a domain to see what it covers and where it fits best.
Ingestion
6 native servicesBatch, CDC, and streaming ingestion.
A production-grade data engineering architecture
Ingestion, transformation, quality, storage, serving, and observability layers. Select a layer to explore its components and design principles.
Transformation Layer
120 pipelinesETL, ELT, and dbt.
- Transformed
- Versioned
- Tested
How we deliver data engineering
Select a delivery track to explore our approach — build, validate, and serve.
Build Pipelines
120 pipelinesBuild ingestion and transformation pipelines.
- Source connectors
- Ingestion design
- ELT with dbt
- Transformations
- Schema management
- Orchestration
- Batch scheduling
- Testing
Data engineering capability depth
Seven capability areas with detailed features — select an area to explore each component and what it delivers.
Ingestion
Batch, CDC, streaming.
- BatchScheduled
- CDCChange capture
- StreamingReal-time
- ConnectorsSources
- APIsPull
- FilesDrop
- SchemaStructure
- EvolutionChange
- ValidationCheck
Start with a focused data engineering assessment
Three assessments that turn data engineering ambition into a reliable platform.
Pipeline Assessment
Assess data pipelines, ETL/ELT, and orchestration.
Duration: 2–3 weeksRequest AssessmentStreaming Readiness
Assess streaming and real-time data readiness.
Duration: 1–2 weeksRequest AssessmentOutcomes our data engineering practice delivers
120 Pipelines
Reliable data pipelines with 99.9% SLA — batch, CDC, and streaming that move 4PB of data reliably for analytics, BI, and AI.
18ms Streaming
Real-time streaming pipelines at 18ms latency with Kafka and Flink — enabling real-time analytics, alerts, and AI on fresh data.
99.2% Quality
Data quality with checks, schema enforcement, and lineage — 99.2% pass rate so data is trusted and traceable end to end.
Continue across the AI & Data ecosystem
Explore related AI & Data capabilities — select one to see its strengths and where it fits.
Data Lakes
Centralised storage.
Insights from our data engineers
Field-tested perspectives on pipelines, streaming, and quality — with author and read time.
Building Reliable Pipelines
ETL/ELT pipelines with 99.9% SLA that move 4PB reliably.
Streaming at 18ms
Kafka and Flink for real-time data at 18ms latency.
Data Quality That Works
Checks, schema enforcement, and lineage that achieve 99.2% quality.
Lakehouse Architecture
Iceberg and Delta lakehouses that unify lakes and warehouses.
Data Lineage End to End
Tracking data lineage and provenance for trust and compliance.
Answers to common data engineering questions
Readiness Score
Your transformation readiness at a glance
- Free 30-minute consultation
- 3-week pipelines
- NDA available on request
- No obligation, no pressure
Ready to build your data pipelines?
Book a consultation with our data engineers and build pipelines, lakes, and streaming that deliver trusted data at 99.9% SLA.