• Build and optimize scalable, maintainable, and high-performance data pipelines and workflows.

• Ingest, transform, and deliver high-volume data from a range of structured and unstructured sources, including MySQL databases and real-time Kafka streams.

• Design and maintain performant data models in Redshift, and optimize SQL queries to support analytics and reporting workloads.

• Contribute to our cloud migration journey and help evolve the data architecture with new ideas and improvements.

• Collaborate with cross-functional, globally distributed teams to translate business requirements into robust technical solutions.

• Embed data quality, reliability, observability, and security as first-class principles across the data platform.

• Support and enhance data solutions operating in a mission-critical payments environment.

• Continuously learn, share knowledge, and help raise standards across data governance, quality, and security practices.

Requirements

• 4-6 years of professional experience in Data Engineering or a related role.

• Strong SQL expertise, including query optimization, complex transformations, and data-modelling.

• Solid Python skills for data engineering and pipeline development.

• Hands-on experience with AWS services such as Redshift, Lambda, Glue, and S3, as well as Airflow for orchestration.

• Familiarity with modern transformation and modelling practices using tools such as dbt.

  • A collaborative mindset, strong problem-solving skills, critical thinking, and a willingness to take ownership and initiative.