Step into a role where your work powers intelligence, innovation, and the future of data‑driven decision‑making. As a Data Engineer, you'll be part of a fast‑moving team architecting the pipelines, platforms, and performance foundations that enable advanced analytics and AI capabilities across the organization.

If you love solving complex problems, building scalable systems, and working with cutting‑edge data technologies, this role puts you at the center of strategic impact.

Key Responsibilities

Design & Engineering

• Build and maintain high‑quality data pipelines across diverse data sources.
• Develop and optimise data warehouses, lakehouses, and large-scale storage solutions.
• Ensure data accuracy, performance, and end-to-end reliability.

Collaboration & Support

• Partner with analysts to translate business needs into technical solutions.
• Provide hands-on support for the data infrastructure, including on-call coverage.
• Apply data security, privacy standards, and compliance best practices.

Continuous Improvement

• Enhance existing pipelines for scalability and efficiency.
• Stay current with emerging data tech and AI foundations to support future AI initiatives.

Tech Stack

Languages & Scripting

• Python, Linux Shell, Bash, PL/SQL

Data Tools & Platforms

• ETL/ELT: Oracle, Airflow, dbt, PySpark, Dremio, Talend
• Databases: Oracle, PostgreSQL, MariaDB, Iceberg/Parquet
• Storage: AWS S3, modern data lakes

Development & BI

• GitLab, Docker, VSCode
• SAP BusinessObjects, Power BI

Collaboration Tools

• JIRA, Confluence, SharePoint

Credentials & Experience

• Bachelor's degree in Computer Science, Engineering, or related field.
• 2+ years of Data Engineering or relevant experience.
• Strong SQL & Python skills, with hands-on data warehousing/lake expertise.
• Experience with tools such as Airflow, dbt, PySpark, and cloud data environments.
• Knowledge of Linux, data modelling, and database administration; telco experience is an asset.