Data Engineer

About the role

We are looking for a Data Engineer to design, build and maintain reliable, scalable data pipelines that enable data‑driven decision making across the organization. You will work with a modern data stack and collaborate closely with business stakeholders to turn raw data into actionable insights and AI‑powered improvements.

Key responsibilities

• Design, develop and operate ETL pipelines and data workflows using Snowflake, AWS, Airflow and dbt.
• Perform data manipulation, transformation and cleansing to ensure accuracy and integrity.
• Implement and optimise database solutions and data models in Snowflake using SQL.
• Leverage AWS services for storage, processing and analytics, and manage cloud resources with Terraform.
• Orchestrate job scheduling and workflow automation with Apache Airflow.
• Create and maintain Looker reports and dashboards.
• Apply AI/ML concepts and AI coding tools (e.g., Claude Code, GitHub Copilot) to improve data workflows and automation.
• Collaborate with cross‑functional teams to continuously improve engineering practices.

Required profile

• Delivers well‑tested, reliable pipelines that scale with business growth.
• Proactively identifies and resolves data quality issues before they impact stakeholders.
• Communicates technical concepts clearly in collaborative settings.
• Balances speed and quality, knowing when to optimise and when to ship.
• Shares knowledge openly and helps elevate team capabilities.

Required skills

• Python (strong programming skills for data engineering).
• SQL (advanced querying and database management).
• Apache Airflow (production experience for workflow orchestration).
• dbt (production experience for modular data transformations).
• Terraform (infrastructure‑as‑code automation).
• AWS services (experience with data‑engineering workloads).
• Snowflake (administration and data modelling experience).
• Looker (reporting and dashboard creation).
• AI coding tools such as Claude Code or GitHub Copilot (daily use).