dataquartz

Data Engineering

Most organisations sit on enormous amounts of data that's siloed, inconsistent, or simply inaccessible to the people who need it. We fix that. Our data engineering practice builds the foundations that unlock analytics, machine learning, and business intelligence — on time, at scale, and with quality you can rely on.

We handle everything from source-to-sink pipeline design to warehouse architecture to real-time streaming infrastructure. Our teams are comfortable with the full modern data stack and work closely with your business and engineering stakeholders to ensure the data you get is the data you actually need.

WHAT WE DELIVER

Concrete outputs, not just advice

Cloud Data Warehouses

Design and implementation of Snowflake, BigQuery, or Redshift warehouses with dimensional modelling, partitioning strategies, and cost-optimised query patterns.

ETL / ELT Pipelines

Reliable, monitored data pipelines that extract from any source — databases, APIs, files, streams — transform with business logic, and load to your target systems.

Data Lake Architecture

Medallion-architecture data lakes on S3, ADLS, or GCS with Delta Lake or Apache Iceberg for ACID transactions, schema evolution, and time travel.

Real-Time Streaming

Apache Kafka and Flink-based streaming pipelines for event-driven architectures, real-time analytics, and low-latency data delivery.

Data Modelling & dbt

Semantic layer design, dbt model development, testing frameworks, and documentation so every metric in your BI tool traces back to a trusted, tested source.

Data Quality & Governance

Automated data quality checks, lineage tracking, cataloguing, and alerting so issues are caught before they reach dashboards or models.

USE CASES

Where we've delivered

RETAIL & E-COMMERCE

Unified customer data platform processing 50M events/day

Built a real-time CDP that consolidates online, in-store, and third-party data into a single customer view powering personalisation and analytics.

FINANCIAL SERVICES

Real-time transaction processing pipeline with sub-100ms latency

Designed a Kafka-based streaming architecture for a fintech client processing millions of transactions per hour with fraud scoring integrated inline.

HEALTHCARE

Clinical data integration across 12 disparate source systems

Delivered a HIPAA-compliant data platform integrating EHR, lab, imaging, and billing data into a unified warehouse for population health analytics.

MEDIA & PUBLISHING

Content analytics pipeline reducing reporting lag from days to minutes

Replaced a batch-based reporting stack with a streaming pipeline that surfaces content performance metrics in near real-time for editorial decisions.

TOOLS & TECHNOLOGIES

Our stack for this service

Apache SparkApache KafkaApache FlinkApache AirflowdbtSnowflakeBigQueryDatabricksDelta LakeApache IcebergFivetranGreat Expectations