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We are seeking a Data Engineer to design, build, and maintain scalable data infrastructure and pipelines that enable analytics, reporting, and machine learning. This role focuses on transforming raw data into structured formats, ensuring data quality, and providing efficient access for business users and data scientists.
Job Responsibility:
Develop and maintain ETL/ELT pipelines for data ingestion and transformation
Design and manage data warehouses, lakes, and distributed systems (e.g., BigQuery, Dataplex)
Conduct data discovery and source system analysis to ensure data is fit for purpose
Implement data validation, cleansing, and transformation processes
Collaborate with stakeholders (BI, CVM, Marketing, Sales, Tech) to gather requirements and deliver solutions
Optimise data workflows for performance and cost efficiency
Support deployment of machine learning models into production environments
Ensure data security and governance compliance
Requirements:
Bachelor’s or Master’s degree in Computer Science, Data Science, Information Technology, or related field
3–4 years of experience in data engineering or related roles
Strong proficiency in SQL, Python, and data modelling
Experience with cloud platforms (GCP, AWS, Azure) and tools like Cloud Composer, Dataflow, Dataproc
Familiarity with distributed computing frameworks (e.g., Apache Beam, Spark)
Knowledge of CI/CD tools (Jenkins, Git, Jira, Confluence)
Understanding of data warehousing concepts and performance tuning
Nice to have:
GCP certification or similar is a plus
What we offer:
Opportunity to work on cutting-edge data engineering projects in a global organisation
Exposure to advanced cloud technologies and distributed systems
Collaborative work environment with cross-functional teams
Career growth and learning opportunities in data and analytics