Data Engineering & Pipelines

We build the pipelines, models, and platforms that turn raw data into a reliable, scalable enterprise asset — ready for analytics and AI.

Engineering

Great data engineering is invisible — until it breaks.

Your analysts, scientists, and executives depend on data that arrives on time, in the right shape, and with quality they can trust. We design and build the engineering foundations that make that happen — pipelines that scale, models that are maintainable, and platforms that your team can actually work with.

Whether you're ingesting millions of events per second or consolidating legacy databases into a modern cloud platform, we bring senior engineering discipline to every layer of the stack.

What We Deliver

ETL/ELT Pipeline Development

We build pipelines that are reliable, observable, and easy to extend. From batch nightly loads to real-time streaming ingestion — we choose the right pattern for your data volume and latency requirements.

Batch and real-time data ingestion from any source
Orchestration with Airflow, dbt Cloud, or cloud-native tools
Error handling, retry logic, and dead-letter queue management
Pipeline monitoring, alerting, and SLA tracking

Data Modelling

Good data models make everything downstream faster and cheaper. We apply proven modelling patterns — dimensional, data vault, or One Big Table — matched to your query patterns and team skills.

Dimensional modelling for analytics and reporting
Data Vault 2.0 for highly regulated environments
One Big Table (OBT) patterns for modern cloud warehouses
Data dictionary and metadata management

Data Quality & Monitoring

We embed quality checks at every stage of the pipeline so problems are caught early, not by your end users. Automated testing, profiling, and alerting give your team confidence in every dataset.

Automated data quality tests with Great Expectations or dbt tests
Data profiling and anomaly detection
Freshness, completeness, and uniqueness monitoring
Quality dashboards and stakeholder reporting

Migration & Modernisation

Moving off legacy systems is high-risk and high-reward. We plan and execute migrations with minimal disruption — validating data at every step and maintaining parallel runs until you're confident in the new platform.

On-premise to cloud migration with zero downtime
Legacy warehouse replacement (Teradata, Netezza, Greenplum)
Schema conversion and data reconciliation
Parallel run strategy and cutover planning

Real-Time Event Streaming

For use cases where minutes matter — clickstream analytics, fraud detection, live operational monitoring — we build streaming pipelines that deliver sub-second data freshness at scale.

Kafka and Kinesis-based event streaming architectures
Stream processing with Spark Structured Streaming or Flink
Change Data Capture (CDC) for near-real-time replication
Real-time feature stores for ML inference pipelines

Managed ELT Ingestion

We connect your SaaS applications, databases, and APIs to your cloud warehouse with managed ingestion — so your team spends time analysing data, not building connectors.