Modern Stack Expertise
Our engineers are certified practitioners on the modern data stack — dbt, Spark, Kafka, Airflow, Snowflake and Databricks — bringing hands-on production expertise, not just theoretical knowledge.
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Data Engineering
Building the data foundations that power AI, analytics and intelligent operations.
Services / Data Engineering
The Data Foundation Every AI Initiative Needs
Great analytics and AI start with great data infrastructure. Sunware's Data Engineering practice designs and builds the pipelines, platforms and data products that feed your analytics and AI initiatives with reliable, high-quality data at scale.
From migrating legacy data warehouses to building modern lakehouse architectures, our data engineers combine deep technical mastery with an understanding of your business domain — so the data flowing through your systems is accurate, timely and fit for purpose.
Talk to a Data Engineer
Lakehouse Architecture
Modern data platforms
Why Partner With Us
What Data Engineering Delivers
for Your Organisation
Four foundational outcomes that make your entire data stack perform.
01
Pipeline Reliability
Well-engineered, monitored data pipelines eliminate the data downtime and silent failures that erode trust in analytics — ensuring your teams always have accurate, fresh data to work with.
02
Infinite Scalability
Cloud-native and lakehouse architectures scale elastically with your data volumes — processing terabytes today and petabytes tomorrow without costly re-architecture or performance degradation.
03
Data Quality
Automated data quality checks, validation rules and anomaly detection catch issues at ingestion — protecting downstream analytics and AI models from garbage-in, garbage-out failures.
04
Faster Insights
Optimised data models, well-structured semantic layers and efficient query engines reduce the time between a business question being asked and a reliable answer being available.
Our Services
Our Data Engineering
Capabilities
Comprehensive data engineering services across the modern data stack.
01 / 06
Data Architecture & Strategy
We design future-proof data architectures — lakehouse, data mesh, lambda and kappa patterns — tailored to your scale, latency requirements, cost constraints and existing technology investments.
02 / 06
ETL/ELT Pipeline Development
We build robust, maintainable data pipelines using dbt, Apache Airflow, Spark and cloud-native services — ingesting, transforming and loading data from hundreds of sources with full lineage tracking.
03 / 06
Data Lakehouse & Warehouse
We implement and optimise modern data platforms on Databricks, Snowflake, BigQuery and Azure Synapse — delivering unified storage and compute that serves both BI and AI workloads efficiently.
04 / 06
Real-Time Streaming
We design and deploy event-driven streaming architectures using Apache Kafka, Flink and cloud messaging services — enabling real-time analytics, fraud detection and operational intelligence.
05 / 06
Data Quality & Observability
We implement Great Expectations, Monte Carlo, Soda and custom quality frameworks that monitor data freshness, completeness, accuracy and schema drift — alerting your team before problems reach production.
06 / 06
DataOps & Automation
We apply DevOps principles to data — CI/CD for pipelines, infrastructure as code, automated testing and version control — reducing deployment risk and accelerating the pace of data delivery.
Why Choose Sunware
Why Engineering Teams Choose Us
Three strengths that define our Data Engineering practice.
Cloud-Agnostic
We design cloud-portable architectures that work across AWS, Azure and GCP — avoiding vendor lock-in and ensuring your data platform can evolve alongside your cloud strategy.
Production-Grade Delivery
We engineer for the real world — with monitoring, alerting, retry logic, schema evolution handling and documented runbooks — so your data platform is operationally robust from day one.