Azure Data Engineer - S

Key Responsibilities

• Design, develop, and maintain scalable data pipelines and integration solutions on Azure.
• Build and optimize data ingestion, transformation, and processing frameworks for structured and unstructured data.
• Develop ETL/ELT workflows using Azure-native services and modern data engineering practices.
• Design and manage enterprise data lakes and data warehouse solutions.
• Collaborate with Data Architects, Data Scientists, Business Analysts, and Application Development teams to deliver data solutions.
• Implement data quality, governance, security, and compliance controls.
• Optimize query performance, data storage, and processing efficiency.
• Monitor and troubleshoot data pipeline performance and production issues.
• Automate data workflows and deployments using DevOps and CI/CD practices.
• Support real-time and batch data processing requirements.
• Create and maintain technical documentation, data models, and operational procedures.
• Participate in Agile development processes, sprint planning, and code reviews.

Required Skills & Qualifications

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
• 6+ years of experience in Data Engineering or related roles.
• Strong hands-on experience with:
• Azure Data Factory (ADF)
• Azure Databricks
• Azure Synapse Analytics
• Azure Data Lake Storage (ADLS)
• Azure SQL Database
• Azure Storage Accounts
• Proficiency in SQL and Python for data processing and transformation.
• Experience building batch and streaming data pipelines.
• Strong understanding of data modeling, data warehousing, and dimensional modeling concepts.
• Experience working with large-scale datasets and distributed computing platforms.
• Knowledge of Spark, PySpark, and Databricks optimization techniques.
• Experience with REST APIs and third-party data integrations.
• Familiarity with Git, Azure DevOps, and CI/CD implementations.
• Understanding of data governance, security, and access management practices.