Data Engineer

About the role

We are seeking an experienced Data Engineer to design, build, and maintain scalable data pipelines that feed our analytics and business intelligence platforms. The role focuses on transforming large raw datasets into reliable, actionable assets using PySpark, Alteryx, and SQL.

Key responsibilities

• Design, develop, and optimise high‑performance distributed pipelines with PySpark for structured and semi‑structured data.
• Automate data workflows and integration solutions using Alteryx Designer.
• Write, tune, and maintain complex SQL queries, stored procedures, and transformations across relational and cloud data warehouses.
• Contribute to data warehouse and data lake modelling, ensuring data quality, availability and performance.
• Monitor, troubleshoot and improve existing ETL/ELT processes.
• Collaborate with analysts, data scientists and business stakeholders to deliver production‑ready datasets.

Required profile

• Bachelor’s or Master’s degree in Computer Science, Information Systems or related field.
• At least 3 years of hands‑on data engineering or big‑data development experience.
• Strong analytical mindset and excellent problem‑solving abilities.
• Effective communication and teamwork skills.

Required skills

• Advanced SQL (query optimisation, data modelling, stored procedures).
• Proficient in PySpark for large‑scale data processing.
• Extensive experience with Alteryx Designer.
• Familiarity with cloud platforms (AWS, Azure, GCP) and their data services.
• Python data libraries such as Pandas and NumPy.
• Workflow orchestration tools like Apache Airflow.
• Understanding of dimensional modelling (Star and Snowflake schemas).