Responsibilities

Design, develop, and maintain efficient data pipelines (ETL/ELT) to ingest, transform, and process large datasets
Build and optimise data models and transformations to ensure data is structured, accurate, and ready for analytics use cases
Support the development and enhancement of modern data platforms, including cloud-based environments (e.g. Databricks or similar ecosystems)
Collaborate with data analysts, engineers, and business stakeholders to translate requirements into scalable data solutions
Ensure strong data quality, reliability, and performance optimisation across pipelines and datasets

Requirements

5-7 years of experience in data engineering or related fields
Strong experience in data pipeline development (ETL/ELT)
Experience with cloud-based data platforms (e.g. Databricks, Snowflake, AWS, Azure, or GCP)
Hands-on experience in data transformation, modelling, and analytics datasets
Proficiency in SQL and/or programming languages such as Python or Scala
Strong analytical thinking and problem-solving skills
Exposure to big data frameworks (e.g. Spark) will be a plus

Data Engineer, Cloud Based Platforms (AWS/ Azure/ GCP / Databricks)