We are looking for a skilled Data Engineer with strong hands-on experience in Azure and Databricks to build scalable data pipelines and optimize data workflows. The ideal candidate will be responsible for designing ETL/ELT processes, transforming and enriching data, handling structured and unstructured datasets, and supporting business analytics through efficient data modeling and performance tuning.
Key Responsibilities
- Design, develop, and maintain scalable ETL/ELT pipelines using Azure Databricks
- Extract, transform, and load data from multiple data sources (structured & unstructured)
- Clean, validate, and enrich data at various processing stages
- Develop and optimize data models (dimensional modeling, star schema, etc.)
- Monitor, troubleshoot, and improve performance of data pipelines and SQL queries
- Ensure data quality, consistency, and governance standards
- Collaborate with BI, analytics, and business stakeholders to understand requirements
- Implement best practices for performance tuning and cost optimization in Azure
Required Skills & Qualifications
- Strong hands-on experience with Azure Databricks
- Good understanding of Azure Data Lake, Azure Data Factory, and related Azure services
- Strong SQL skills (complex joins, aggregations, query optimization)
- Experience with PySpark / Apache Spark
- Experience building and maintaining ETL/ELT workflows
- Knowledge of data modeling concepts
- Experience handling unstructured textual data
- Strong analytical and problem-solving skills
Good to Have
- Experience with Delta Lake
- CI/CD experience for data pipelines
- Knowledge of data governance and security best practices
- Exposure to cloud data warehousing solutions
Skills: lake,data bricks,azure,data modeling
