Data Engineer
Summary
Designs and builds scalable ETL/ELT pipelines using Azure Data Factory and Snowflake to feed analytics and BI systems.
We are seeking a highly skilled and experienced Data Engineer with strong expertise in Snowflake, ETL processes, Microsoft Azure, and Azure Data Factory (ADF). The ideal candidate will be responsible for designing, building, and optimizing scalable data pipelines and data solutions to support business intelligence, analytics, and data-driven decision-making. Key Responsibilities
- Design, develop, and maintain scalable and efficient ETL/ELT pipelines using Azure Data Factory (ADF) and other Azure services
- Build and optimize data solutions leveraging Snowflake as the cloud data warehouse
- Integrate data from multiple sources, ensuring high data quality, reliability, and performance
- Develop and manage data workflows, transformations, and orchestration processes
- Collaborate with data analysts, data scientists, and business stakeholders to understand data requirements
- Optimize data storage, query performance, and cost efficiency in Snowflake
- Implement data governance, security, and compliance best practices
- Monitor, troubleshoot, and enhance existing data pipelines and workflows
- Support real-time and batch data processing requirements
- Maintain proper documentation for data architecture, pipelines, and processes
- 8+ years of experience in Data Engineering / Data Warehousing
- Strong hands-on experience with Snowflake (data modeling, performance tuning, SnowSQL, etc.)
- Expertise in Azure Data Factory (ADF) for building and orchestrating data pipelines
- Solid understanding of ETL/ELT concepts and tools
- Experience with Microsoft Azure ecosystem (Azure Data Lake, Azure SQL, Synapse, etc.)
- Proficiency in SQL and data modeling techniques
- Experience with scripting languages such as Python or Shell scripting
- Knowledge of data integration, transformation, and data quality practices
- Strong problem-solving and analytical skills
- Experience with Databricks or Spark
- Familiarity with CI/CD pipelines and DevOps practices in Azure
- Exposure to real-time data processing
- Understanding of data governance and security frameworks