Senior Azure Data Engineer (ID: 3508)

As a Senior Azure Data Engineer, you will:

• Design and implement scalable data solutions based on high-level architecture.
• Build and optimize end-to-end data pipelines using Azure Databricks.
• Load and process data from disparate data sources into centralized platforms.
• Perform preprocessing, transformation, and enrichment using PySpark and Spark-SQL.
• Work directly with stakeholders to gather business requirements for data pipeline and lake migration initiatives.
• Develop and maintain data solutions using Azure services such as ADLS, ADF, Cosmos DB, and Azure SQL DW.
• Implement serverless architectures using Azure Functions.
• Monitor and manage Azure DevOps and Databricks pipelines.
• Participate in production support and incident resolution.
• Contribute to data governance practices using Unity Catalog.
• Support ARM template-based infrastructure deployments.
• Continuously improve pipeline performance, reliability, and scalability.

What You Bring to the Table:

• 8-10 years of hands‑on experience in data engineering and Azure ecosystem.
• Strong expertise in Python and Scala for data processing.
• Deep knowledge of SQL and NoSQL databases.
• Advanced experience with PySpark and Spark-SQL.
• Strong hands‑on experience with Azure Databricks.
• Practical experience with Azure Data Lake Storage (ADLS) and Azure Data Factory (ADF).
• Experience working with Stream Analytics, SQL Data Warehouse, and Cosmos DB.
• Solid exposure to Azure DevOps practices.

You should possess the ability to:

• Design independent solutions from high‑level architecture without constant supervision.
• Translate business requirements into technical data solutions.
• Handle complex data ingestion from multiple heterogeneous sources.
• Optimize Spark workloads for performance and cost efficiency.
• Monitor and troubleshoot production pipelines effectively.
• Collaborate cross‑functionally with business and technical stakeholders.
• Implement data governance and access control using Unity Catalog.
• Automate deployments using DevOps and Infrastructure-as-Code practices.

What We Bring to the Table:

• Opportunity to work on large‑scale Azure data transformation projects.
• Exposure to modern cloud‑native and serverless architecture.
• Collaborative environment with cross‑functional stakeholders.
• Ownership‑driven culture where independent solution design is valued.
• Hands‑on experience with enterprise‑grade data platforms.
• Involvement in cloud migration and lakehouse implementations.

Let's Connect!

Want to discuss this opportunity in more detail? Feel free to reach out.