Source description
About the role
Summary: Build and maintain scalable data pipelines, warehouses, and lakes to ensure accurate, accessible, and secure data for analytics and reporting. Key Responsibilities: Develop and optimise data pipelines and ETL/ELT processes. Build and maintain data warehouse and data lake structures. Ensure data quality, governance, and security across platforms. Collaborate with data scientists and engineering teams. Monitor performance and troubleshoot data workflows. Skills Required: Strong SQL, Python, Spark, Redshift. Experience with cloud data platforms (AWS/Azure). Preferably AWS. Knowledge of data modelling, governance, and metadata. Understanding of large-scale distributed data systems. Key Responsibilities: Develop and optimise data pipelines and ETL/ELT processes. Build and maintain data warehouse and data lake structures. Ensure data quality, governance, and security across platforms. Collaborate with data scientists and engineering teams. Monitor performance and troubleshoot data workflows. Graduate in Computer Science, Data Science, or related field. 3-4 years of experience in data engineering or a related field. Skills Required: Strong SQL, Python, Spark, Redshift. Experience with cloud data platforms (AWS/Azure). Preferably AWS. Knowledge of data modelling, governance, and metadata. Understanding of large-scale distributed data systems.
More at EXL