Data engineering.

Design and operate data pipelines that ingest transactional data from point-of-sale systems, supply chain platforms, and payment processors.

Build and maintain the data warehouse: schema design, transformation layers, and automated quality checks.

Produce dashboards and reporting systems for retailers, hospitality operators, and warehouse teams.

Implement real-time synchronisation between distributed outlets and central reporting systems.

Establish monitoring, alerting, and data quality frameworks across the pipeline estate.

Engage directly with clients to translate operational reporting requirements into data models.

Strong SQL practice, including complex query authoring, query optimisation, and schema design from first principles.

Working experience with at least one data orchestration tool such as Apache Airflow, Dagster, or Prefect.

Python fluency for data transformation, scripting, and automation tasks.

Understanding of dimensional modelling and warehouse design patterns.

Practical orientation toward data products rather than pipelines alone: dashboards, alerts, and reports that are actively used.

Python

SQL

dbt

Apache Airflow

PostgreSQL

BigQuery

Metabase

Docker

Terraform

GitHub Actions