Data Engineer
23 hours ago
Key accountabilities
- Focuses on implementing the architect's 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 architect's
blueprints.
- Outputs include functional data pipelines, optimized databases, and automated workflows
Skills and Experience | Essential
- 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 it's 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
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