Description :

Role Overview :

You will be responsible for building modern, scalable, and high-performance data architectures on the Azure Cloud.

The focus is on leveraging the integration and unified experience provided by the Fabric Platform to deliver end-to-end data engineering solutions, from ingestion and transformation to warehousing and consumption.

Mandatory Skills & Core Technical Competencies :

The ideal candidate must possess deep, hands-on proficiency in the following areas :

Overall Experience : 6+ years of professional experience in data engineering, with a strong focus on cloud-based solutions.

Azure Fabric Platform Expertise : Mandatory hands-on expertise in developing solutions that integrate and utilize core Azure components within the unified Fabric platform.

This includes :

- Azure Synapse Analytics (SQL Pools, Serverless, Spark Pools).

- Azure Databricks (Development and optimization).

- Azure Data Factory (ADF) (Pipeline design, configuration, and monitoring).

- Azure Blob Storage (Data Lake design and management).

- Azure SQL DB (Relational data storage and querying).

Project Implementation : Proven track record of 23 successful, end-to-end Azure Data project implementations with significant hands-on contributions.

Coding & Scripting : Strong knowledge of Python / PySpark for scalable data transformation, cleansing, and processing within Databricks and Synapse Spark environments.

Database Skills : Excellent, advanced proficiency in Azure SQL development, including T-SQL, performance tuning, stored procedures, and complex data modeling.

Architectural Design : Demonstrated ability to design modern data architectures (e.g., Lakehouse, Data Mesh) using Azure Cloud services, ensuring solutions are scalable, secure, and cost-effective.

Enterprise Deployment : Experience designing and deploying robust, scalable, enterprise-wide cloud data solutions from development through to production environments.

Candidate Profile :

- Strong analytical and problem-solving skills to troubleshoot complex data pipeline issues.

- Excellent communication skills for collaborating with business stakeholders, data scientists, and cross-functional engineering teams.

- Ability to work independently and manage deliverables within the specified shift timing