Senior Azure Data Engineer - ETL (5-7 yrs)

Key Responsibilities :

- Design, develop, and maintain robust data pipelines and ETL processes using Azure Data Factory, Databricks, and related Azure services.

- Architect and implement scalable data solutions using Azure Synapse Analytics, Azure Data Lake Storage, and Azure SQL Database.

- Collaborate with data analysts, data scientists, and business stakeholders to understand data needs and deliver solutions that drive insights and innovation.

- Manage and optimize data ingestion and transformation processes for batch and streaming data.

- Ensure data quality, consistency, and security by implementing best practices and governance policies.

- Develop and enforce standards for coding, performance, and data management practices.

- Utilize Databricks for advanced data processing and machine learning model integration.

- Monitor and troubleshoot data pipeline performance issues to ensure system reliability and uptime.

- Stay updated with the latest Azure and data engineering technologies to continuously improve processes.

Required Qualifications :

- Azure Data Engineering Associate Certification (DP-203).

- Databricks Data Engineering Certification.

- 5+ years of hands-on experience in data engineering, with a focus on Azure-based solutions.

- Strong proficiency in Azure Data Factory, Azure Synapse Analytics, Azure Data Lake, and Azure SQL Database.

- Expertise in Databricks, Spark, and Python or Scala for big data processing.

- Proficiency in Azure DevOps for CI/CD pipelines and version control.

- Solid understanding of data modeling, data warehousing, and data architecture principles.

- Experience with streaming data solutions using Azure Event Hub or Azure Stream Analytics.

- Strong knowledge of data security, access controls, and compliance frameworks.

- Excellent problem-solving and communication skills