Cloud Migration and Data Engineering Services in Saudi Arabia
End-to-end cloud strategy, data engineering, and analytics — from multi-cloud architecture to real-time pipelines and AI-ready infrastructure. Built to migrate, modernize, and deliver measurable outcomes.
Enterprises are drowning in data they can't use and cloud costs they can't justify.
Disconnected systems, ungoverned data lakes, and ad-hoc cloud migrations create complexity without clarity. We architect the full stack — from ingestion to insight — with precision and purpose.
Six capabilities. One integrated cloud & data engine.
From cloud foundation to real-time intelligence — modular services that compose into a complete enterprise data platform.
Cloud Strategy & Migration
Assess your estate, design the target architecture, and execute zero-downtime migrations to AWS, Azure, or GCP — with governance and cost guardrails built in.
Data Engineering & Pipelines
Design and operate batch and streaming data pipelines — Kafka, Spark, dbt, Airflow — connecting every source to a clean, reliable data layer your teams can trust.
Analytics & Business Intelligence
Turn raw data into executive-grade dashboards and self-service analytics. We build semantic layers, data models, and embedded BI that make insight accessible to everyone.
MLOps & AI Infrastructure
Build the data and compute infrastructure that modern AI demands — feature stores, model registries, training pipelines, and production serving with full observability.
Data Lakehouse & Platform
Design and implement a modern data lakehouse on Delta Lake, Apache Iceberg, or Snowflake — unified storage, open formats, ACID transactions, and zero data silos.
Data Governance & Security
Implement end-to-end data cataloguing, lineage tracking, access control, and regulatory compliance — so every data asset is discoverable, trusted, and protected.
Migrate with confidence. Operate with control.
We de-risk cloud migrations with a proven 5-step framework: assess, design, migrate, validate, optimise. No lift-and-shift shortcuts — every workload is right-sized and cost-governed from day one.
Cloud-agnostic. Best-of-breed stack.
We select the right tools for your workload — not our partnerships. Certified engineers across every major platform.
Start anywhere. Scale to everything.
Whether you need a rapid cloud assessment, a full data platform build, or embedded engineers in your team — we adapt to your context.
Cloud Assessment
A rapid 4-week workload inventory, architecture review, and cost-optimisation roadmap.
4 weeksMigration Sprint
Wave-based migration with our factory model — parallel run, validate, cutover.
8–16 weeksData Platform Build
End-to-end lakehouse or warehouse design, pipeline engineering, and BI layer delivery.
12–24 weeksEmbedded Engineering
Senior cloud and data engineers placed directly in your team — on-demand capacity.
OngoingReady to transform your cloud and data capabilities?
From cloud migration to real-time analytics — Nehlum engineers your full data stack. No guesswork. No vendor lock-in.
Frequently asked questions
Which cloud platforms and cloud models does Nehlum support?
Nehlum is cloud-agnostic and has certified engineers on AWS, Microsoft Azure, and Google Cloud. It supports public cloud on those three providers, private cloud on-premises or in dedicated hosting, hybrid cloud with unified control across on-premises and cloud, and multi-cloud with best-of-breed services across providers under unified operations. Tools are selected for your workload, not for Nehlum's partnerships.
How does Nehlum migrate workloads to the cloud?
Nehlum uses a five-step framework: assess, design, migrate, validate, and optimise. It inventories workloads, dependencies, and total cost of ownership; designs the target architecture, landing zone, security, and network topology; migrates in waves with parallel run validation; validates performance, security, and cutover readiness; and sets a FinOps baseline with continuous cost governance. There are no lift-and-shift shortcuts, and every workload is right-sized from day one.
How long do cloud migration and data platform projects take?
It depends on where you start. A cloud assessment is a rapid 4-week workload inventory, architecture review, and cost-optimisation roadmap. A migration sprint runs 8 to 16 weeks using a wave-based factory model. A data platform build, covering lakehouse or warehouse design, pipeline engineering, and the BI layer, runs 12 to 24 weeks. Nehlum can also place senior cloud and data engineers directly in your team on an ongoing basis.
Which data engineering tools and architecture does Nehlum use?
Nehlum builds batch and streaming pipelines with Kafka, Spark, dbt, and Airflow, alongside Fivetran, Debezium, and Flink. Data moves through a four-layer architecture: ingest, transform, store, and serve. Storage is typically a lakehouse on Snowflake, Databricks, Delta Lake, or Apache Iceberg, organised into raw, curated, semantic, and AI feature zones, with insight served through Power BI, Looker, Tableau, or REST APIs.
How does Nehlum handle data governance, security, and compliance?
Governance and compliance are designed in rather than added later. Nehlum implements end-to-end data cataloguing, lineage tracking, access control, and regulatory compliance, including PDPL, so every data asset is discoverable, trusted, and protected. It works with tools such as Unity Catalog and Purview, and builds governance and cost guardrails into cloud migrations, with security covered in both the design and validation steps.