Senior Azure Data Engineer

Greetings from TCS!

Job Title: Senior Azure Data Engineer

Required Skillset: Azure data factory, data bricks, data lake, automation and performance optimization of ETL.

Location: Gurugram

Experience Range: 6-8 years

Job Description

Must-Have**

• Good Knowledge of Data Brick lakehouse and Azure DataLake concept Knowledge of Data Bricks delta concept
• Delta live tables (DLT)
• Strong hands-on experience in ELT pipeline development using Azure Data factory and Databricks Autoloader, Notebook scripting and Azure Synapse Activity Copy, Data Flow Task
• Strong knowledge of metadata-driven data pipeline, metadata management, dynamic logic
• In-depth knowledge of data storage solutions, including Azure Data Lake Storage (ADLS), and Azure Serverless SQL Pool.
• Experience with data transformation using Spark, and SQL technologies. Solid understanding of design patterns, and best practices of the cloud stack.
• Experience with code management and version control using Git or similar tools.
• Strong problem-solving and debugging skills in ETL workflows and data pipelines.
• Strong understanding of Azure Data bricks and Azure Synapse internals features and capabilities.
• Knowledge of Azure DevOps and continuous integration and deployment (CI/CD) process.
• Knowledge of data quality and data profiling techniques, with experience in data validation and data cleansing

Good To Have:

1. Power Shell Knowledge
2. Power BI Knowledge

Responsibility of / Expectations from the Role:

• Conducting technical sessions, design reviews, code reviews, and demos of pipelines and their functionality
• Developing technical specification for Data pipelines and workflow and getting sign-off from Architect and Stryker leads.
• Developing, deploying, and maintaining workflows and data pipelines using Azure Data bricks and Azure Synapse.
• Developing pipeline/notebook for Delta live tables ( DLT) Databricks Auto Loader, Notebook scripting and Azure Synapse Activity Copy, Data Flow Task
• Writing efficient and high-performing ETL code using PySpark, and SQL technologies.

Thanks & Regards,

Ria Aarthi A.