Hiring For Data Engineer

Requirement:

• Provide Big Data Solution Architecture advisory; this includes infrastructure, networking, cloud computing best practices, ingestion (streaming or batches) and implementation guidance.
• Understand SPs overall data estate, IT and business priorities and success measures to design implementation architectures and solutions.
• Familiarity with the current Azure Data Tech Stack (e.g. SQL Server, Azure Synapse, Azure ML Studio, Azure Data Factory, Big Data, Data Lake, Azure Databricks, Fabric, Purview, IOT Hub etc.)
• Implemented solution with cost and compute monitoring thoroughly considered; Platform runs a charge back to customer model.
• Ensure that solution exhibits high levels of performance, security, scalability, maintainability, appropriate reusability, and reliability upon deployment.
• Maintain technical skills and knowledge, keeping up to date with market trends and competitive insights to inform improvement opportunities to the platform; not limited to Azure.
• Implement solution with CI/CD and BAU long-term maintenance in mind.
• Familiarity with analytical warehouse
• Maintains cost-efficiency and compute-efficiency mindset
• Point of Contact for SOW CRs that needs to be implemented into DataFabricks from time to time:
• New Data Sources of different architecture types (pub-sub, DBs, APIs, etc.)
• Maintenance and refresh rates of data sources
• Includes overseeing the Senior Data Engineer and the Data Engineering Scrum Team
• Provide review and approval to Data Modelling pipelines that feed into Data Marts/Fabric DataFlows that are fed to Fabric Dashboards or ML use cases