Data Engineer

Key Accountabilities

• Focuses on implementing the architects designs by building, maintaining, and optimizing the data pipelines

and infrastructure required for data storage and processing

• Works hands-on, diving deep into the code and tools to implement the data infrastructure and address day-

to-day technical challenges.

• Writes and maintains ETL (Extract, Transform, Load) pipelines.
• Builds systems to move and process data efficiently.
• Implements and monitors data systems for performance and reliability.
• Works closely with data architects and analysts to implement and optimize systems based on the architects

blueprints.

• Outputs include functional data pipelines, optimized databases, and automated workflows

• Experience as implementing Data solutions also experience in

implementing and managing data solution using Microsoft Azure

• Proficient in programming languages like Python (preferable) or C#,
• Strong understanding of Data modelling (star schema/ snowflake schema)
• Strong understanding dataflow/power Query, DAX query , SQL, KQL
• Hands-on experience of Azure Data services such as Power BI for Visualisation, Azure Synapse (or AAS) for

analytics , Azure Data Factory for ETL/Pipeline, Azure Data Lake Storage Gen 1/ Gen 2 , Azure Blob for

storage & warehouse.

• Mandatory knowledge of using Microsoft Fabric (or Azure Synapse) and its components such as notebooks,

shortcuts, data lake and data warehouse

Skills and Experience | Desired

• Hands-on understanding of Power BI (or similar like Tableau).
• Knowledge in other data platform such as Snowflake , Databrick is plus
• Microsoft certified Fabric DP-600 or DP-700 is big plus , plus any other relevant Azure Data certification is

advantage