Engineering Services
Data Platform
& Architecture.
We design and build the cloud-native data infrastructure that powers modern, analytics-at-scale enterprises. From lakehouse architectures on AWS, Azure, or GCP, to real-time streaming pipelines capable of processing millions of events per second, we engineer platforms that are performant, cost-optimised, and built to outlast the change cycle.
Core Capabilities
Lakehouse Architecture
Design of unified storage architectures using Delta Lake, Apache Iceberg, or Apache Hudi that eliminate the data lake vs warehouse tradeoff and support ACID transactions at petabyte scale.
Cloud Data Warehouse
Implementation and optimisation of Snowflake, BigQuery, and Redshift environments—including query cost governance, workload management, and near-zero-downtime migrations from on-premise systems.
Real-Time Streaming Pipelines
Engineering of event-driven architectures using Apache Kafka, AWS Kinesis, or Google Pub/Sub for sub-second latency data ingestion and processing with Apache Flink or Spark Structured Streaming.
Data Mesh Implementation
Decentralised data platform delivery using domain-oriented ownership with self-serve infrastructure and federated computational governance—enabling teams to publish and consume data as products.
DataOps & Pipeline Orchestration
Deployment of modern orchestration frameworks—Apache Airflow, Prefect, Dagster—with CI/CD, automated testing, and observability baked into every pipeline from day one.
Cost Engineering & FinOps
Continuous cost optimisation of compute and storage through intelligent autoscaling, tiered storage policies, and query profiling—typically achieving 30–40% reduction in cloud spend.
Our Methodology
Architecture Design
A vendor-agnostic Architecture Design Review producing a detailed reference architecture, infrastructure blueprint, and cost model for your target platform state, driven by your data volume, latency, and access-pattern requirements.
Foundation Build
Infrastructure-as-Code delivery (Terraform / Pulumi) establishing core platform layers: ingestion, storage, transformation, and serving. All components deployed within your cloud account with full handover documentation.
Migration & Onboarding
Structured migration of existing data sources, pipelines, and user workloads onto the new platform with zero-downtime cutovers, automated validation checks, and rollback playbooks.
Operationalise & Optimise
Embedding platform observability (data freshness, pipeline SLAs, cost dashboards) and running quarterly architectural reviews to rightsize compute and incorporate emerging cloud primitives.
Measurable Outcomes
10x improvement in query performance for analytical workloads through columnar storage and intelligent caching.
30–40% reduction in total data infrastructure cost within the first 12 months post-migration.
Pipeline reliability exceeding 99.9% SLA through automated recovery, alerting, and data quality gates.
Data freshness reduced from batch-daily to near-real-time (< 5-minute latency) for operational reports.
Full infrastructure managed as code with reproducible environments and zero manual provisioning drift.
Ready to modernise your data infrastructure?
Let's architect a solution built precisely for your enterprise requirements.