Senior Data Engineer

Overview

• Lead the design and implementation of Azure-based data solutions, ensuring scalability and performance optimization.
• Collaborate with cross-functional teams to define data sources and business rules for analytics-ready datasets.
• Develop and maintain ETL/ELT pipelines using Azure-native tools and frameworks.
• Optimize SQL queries and distributed Spark workloads for enhanced data processing efficiency.
• Support production environments, troubleshoot issues, and ensure data integrity and security.
• Participate in continuous improvement initiatives to enhance team collaboration and engineering excellence.
• Contribute to the development and deployment of machine learning models within Azure environments.
• Ensure adherence to enterprise data governance standards and solution delivery frameworks.

Key Responsibilities & Duties

• Architect and build real-time and batch data integrations into Azure Data Lake Storage and Azure SQL/Synapse.
• Develop reusable frameworks for data ingestion, transformation, and delivery using SQL, PySpark, and Azure Databricks.
• Create enterprise-grade data models and transform raw data into analytics-ready structures.
• Execute Azure DevOps CI/CD pipelines, including branching strategies and production migrations.
• Participate in 24×7 on-call support, resolving critical data pipeline issues.
• Implement data quality checks and collaborate with data stewards to maintain data integrity.
• Translate business problems into scalable analytical solutions using Power BI and AI/ML models.
• Contribute to team development by promoting engineering excellence and adhering to governance standards.

Job Requirements

• Bachelor’s degree in Computer Science, Software Engineering, or equivalent experience.
• Minimum 5 years of hands-on experience building Azure data solutions.
• Proficiency in SQL development across SQL Server, Oracle, and DB2.
• Experience with Azure-native tools like Data Factory, Databricks, and Synapse.
• Knowledge of Power BI and exposure to streaming technologies such as Kafka.
• Strong background in ETL/ELT pipeline development and cloud data engineering.
• Familiarity with CRM systems like Salesforce and supply chain domains is a plus.
• Ability to manage multiple priorities in a fast-paced environment and communicate effectively.