Data Engineer – Build Scalable Data Pipelines

About the role

We are looking for a Data Engineer to design, build, and maintain scalable data pipelines that support both batch and real-time processing. The role works closely with product, engineering, and analytics teams to ensure data reliability and enable data-driven decision making.

Key responsibilities

• Design, develop, and operate ETL/ELT pipelines on AWS.
• Build and optimise data lakes, warehouses and data models (Redshift, PostgreSQL/Aurora, MySQL/MariaDB).
• Ensure data quality, reliability and integrity across all systems.
• Collaborate with cross-functional teams to define data requirements and deliver solutions.
• Implement real-time streaming solutions and batch processing workflows using tools such as Kafka and Airflow.
• Monitor and improve database performance and query efficiency.
• Apply data governance, security and best-practice standards.
• Mentor junior engineers and promote engineering excellence.

Required profile

• 5+ years of experience in data engineering or a related field.
• Strong problem-solving skills in a fast-moving product environment.
• Ability to design reusable, tested pipeline code.

Required skills

• Python
• SQL
• AWS services: Redshift, S3, Athena, ECS, EventBridge
• Workflow orchestration: Airflow (or equivalent)
• Relational databases: PostgreSQL/Aurora, MySQL/MariaDB
• Data modelling, dimensional design and schema evolution
• Kafka (streaming) – a plus