Responsibilities
- Create and maintain data architectures.
- Build and maintain platforms required for storage, extraction, transformation, and loading of data from a wide variety of data sources.
- Improve discoverability and distribution of analytical data to data analysts and data scientists.
- Implement best practices in data security throughout the lifecycle of analytical data.
Requirements
- Background in Information Systems (IS), Computer Science or related field in a reputed institution.
- Experience in designing and maintaining data platforms such as data lakes, data warehouses and the associated data pipelines.
- Proficient in creating and maintaining complex data pipelines using tools such as Microsoft SQL Server Integration Services (SSIS).
- Experience in Commercial Cloud such as Amazon web Services (AWS), Google cloud Platform (GCP) and Microsoft Azure.
- Knowledge of data platforms such as Spark, Flink, Kafka, SQL and NoSQL databases, Airflow.
- Knowledge of the latest developments in data engineering and best practices in data management.
- Knowledge of cloud technologies in data platforms is a plus e.g., Snowflake, AWS Redshift, Google Big Query, Azure Synapse.
