Azure Data Engineer

Role & responsibilities

• Design & Develop: Create scalable data ingestion, transformation, and loading (ETL/ELT) pipelines using Azure services and SSIS.
• Build Data Pipelines: Implement data flows for batch and streaming data, integrating various sources.
• Manage Data Storage: Design and manage data solutions in Azure Data Lake Storage (ADLS), Azure SQL Database, Synapse, or Fabric.
• Utilize Azure Tools: Proficiently use Azure Data Factory (ADF), Logic APP, SSIS and Power BI.
• Leverage SSIS: Develop, deploy, and maintain SSIS packages for complex data movements, often migrating to Azure.
• Ensure Data Quality: Implement data validation, cleansing, and governance.
• Collaborate: Work with analysts, and stakeholders to understand data needs.
• Optimize Performance: Tune pipelines and data stores for efficiency and cost effectiveness.

Preferred candidate profile

• Bachelors degree in computer science, Information Technology, or a related field.
• 5+ years of experience in data engineering with a focus on Azure cloud services.
• Proficiency in Azure Data Factory, Azure Synapse Analytics, and Azure SQL Database.
• Strong experience with SQL, Python, or other scripting languages.
• Familiarity with data modeling, ETL design, and big data tools such as Hadoop or Spark.
• Experience with data warehousing concepts, data lakes, and data pipelines.
• Understanding of data governance, data quality, and security best practices.
• Excellent problem-solving skills and ability to work in a fast-paced, collaborative environment. Key Skills & Technologies
• Azure: Data Factory, Data Lake (ADLS Gen2), Azure SQL, Logic APP, Azure log analytics
• SSIS: Good Knowledge in SSIS (Control Flow, Data Flow, Transformations).
• Databases: Good knowledge of SQL DB and writing querie