Data Engineer

Mandatory Skills -

DAX, Power BI

ADF, Databricks

Synapse

Semantic layers

Snowflake

Star Schema

Job Description:

• Design and develop robust, scalable data pipelines using Azure Data Factory and Azure Databricks.
• Build and maintain data models (including tabular and semantic models) for analytics and reporting across business domains.
• Develop and optimize SQL and PySpark scripts for data ingestion, transformation, and quality checks.
• Leverage Azure Synapse Analytics for data warehousing solutions and advanced data querying.
• Integrate data from various sources into centralized data repositories to support business intelligence use cases.
• Create and manage Power BI datasets, dashboards, and reports, including DAX calculations and measures.
• Work closely with BI developers, analysts, and stakeholders to understand reporting requirements and deliver reliable data solutions.
• Ensure data quality, integrity, and governance across all data flows and semantic layers.
• Optimize performance of tabular models and analytical queries in Power BI and Synapse.
• Participate in code reviews, documentation, and CI/CD processes to maintain high-quality engineering standards.

Required Skills & Qualifications:

• Experience in data engineering or related field.
• Strong knowledge of Azure Data Services including Azure Data Factory, Azure Databricks, and Synapse Analytics.
• Hands-on experience with Power BI, including DAX, Power Query, and semantic model design.
• Proficiency in SQL and Python, with experience using PySpark for large-scale data processing.
• Solid understanding of data warehousing concepts, dimensional modeling, and best practices for ETL/ELT pipelines.
• Experience working with tabular models (SSAS/Power BI) and managing semantic layers.
• Familiarity with version control tools (e.g., Git) and agile development practices.