Azure Data Engineer

Company Name: Confidential

Job Title: Azure Data Engineer

Qualification: Any graduation

Experience: 6 to 16 years

Must Have Skills:

Azure Data Factory (ADF): Expertise in building and orchestrating data pipelines using Azure Data Factory.
Azure Synapse Analytics / Azure SQL / SQL Server: Proficient in writing complex T-SQL queries, stored procedures, and performance tuning.
Azure Data Lake Storage (Gen2): Experience with hierarchical namespace, security, and integrating with ADF.
Data Modeling & ETL Development: Strong experience in dimensional modeling, building data warehouses, and developing ETL/ELT processes.
Programming with PySpark / Python / Scala: Hands-on experience in processing big data using Databricks or HDInsight with Spark.

Good to Have Skills:

Azure Databricks: Experience in building data pipelines and ML workflows in Databricks notebooks.
DevOps (CI/CD for Data Pipelines): Familiarity with Azure DevOps or GitHub Actions for managing deployment pipelines.
Monitoring & Logging: Understanding of Azure Monitor, Log Analytics, and ADF pipeline monitoring.
Power BI or Other BI Tools: Basic knowledge of reporting tools to support data visualization.
Security & Governance: Knowledge of RBAC, data masking, encryption, and Purview for data governance.

Roles and Responsibilities:

Design and Develop Data Pipelines: Build scalable and efficient data pipelines using Azure Data Factory, Data Lake, and Synapse Analytics.
Data Integration and Transformation: Extract, transform, and load data from various structured and unstructured data sources.
Work with Cross-Functional Teams: Collaborate with data scientists, analysts, and business stakeholders to understand data requirements.
Data Modeling & Optimization: Design and implement logical and physical data models; tune queries and pipelines for performance.
Deployment & Automation: Implement CI/CD pipelines for automated testing and deployment of data workflows.
Monitoring & Troubleshooting: Monitor data pipelines and resolve issues related to performance, failures, or data quality.
Documentation & Best Practices: Maintain technical documentation and follow industry best practices in coding and data management.

Location: Pan India

CTC Range: 24 to 35 LPA

Notice period: Immediate

Mode of Interview: Virtual