Sr. Data Engineer

- Diagnose and resolve pipeline failures, logic errors, and performance bottlenecks across the data engineering lifecycle. - Automate repetitive data processes using Azure Functions, Logic Apps, PowerShell, or Python scripting within the Fabric ecosystem. - Collaborate with stakeholders to gather business requirements and translate them into scalable data solutions.

Key Responsibilities: - Hands-on experience building and maintaining OLTP databases, including relational data modeling, schema design, normalization, SQL query development, indexing, transaction handling, performance troubleshooting, and data integrity controls - Design, develop, and maintain Power BI reports, dashboards, DAX expressions, KPIs, and scorecards using both Import and DirectQuery modes.

- Build and orchestrate scalable ETL/ELT workflows using Fabric Data Pipelines, Dataflows Gen2, and Azure Data Factory. - Write and tune complex T-SQL and KQL queries, stored procedures, and views for performance in Synapse SQL and SQL Server environments. - Implement data models based on star/snowflake schemas and support modern data warehousing and Lakehouse architectures using Microsoft Fabric.

- Implement data models based on star/snowflake schemas and support modern data warehousing and Lakehouse architectures using Microsoft Fabric. - Manage and optimize Azure SQL application databases, including schema design, indexing strategies, stored procedures, query optimization, data integrity, security, monitoring, backup/recovery awareness, and operational reliability for client-facing business applications. - Partner with application, analytics, and client teams to ensure Azure SQL transactional databases are performant, secure, well-structured, and ready for integration with reporting, data warehousing, Microsoft Fabric, and AI/ML workloads.

- Manage and optimize Azure SQL application databases, including schema design, indexing strategies, stored procedures, query optimization, data integrity, security, monitoring, backup/recovery awareness, and operational reliability for client-facing business applications. - Partner with application, analytics, and client teams to ensure Azure SQL transactional databases are performant, secure, well-structured, and ready for integration with reporting, data warehousing, Microsoft Fabric, and AI/ML workloads. - integrate structured and unstructured data sources (e.g., SQL, Excel, APIs, Blob Storage), and transform them efficiently using Fabric Notebooks (Spark/PySpark) or Dataflows.

- Partner with application, analytics, and client teams to ensure Azure SQL transactional databases are performant, secure, well-structured, and ready for integration with reporting, data warehousing, Microsoft Fabric, and AI/ML workloads. - integrate structured and unstructured data sources (e.g., SQL, Excel, APIs, Blob Storage), and transform them efficiently using Fabric Notebooks (Spark/PySpark) or Dataflows. - Diagnose and resolve pipeline failures, logic errors, and performance bottlenecks across the data engineering lifecycle.

- Apply best practices for item-level security, workspace-based access models, and data lineage using Microsoft One Lake and Fabric tools. - Utilized AI-assisted tools such as GitHub Copilot and Microsoft Copilot to accelerate SQL development, data pipeline implementation, code reviews, troubleshooting, and performance optimization. - Support AI initiatives by preparing, transforming, and managing high-quality datasets for model training and inference.

- Demonstrated hands-on experience in Power BI development and data engineering, including building enterprise dashboards and semantic models, developing DAX calculations, implementing ETL/ELT pipelines, integrating multiple data sources, optimizing data models and queries, and supporting production data workloads. - Strong expertise in T-SQL and KQL, with demonstrated query optimization skills. - Hands-on experience managing Azure SQL Database environments, including performance tuning, index optimization, stored procedures, query troubleshooting, database security, and operational support for application workloads.

- Strong expertise in T-SQL and KQL, with demonstrated query optimization skills. - Hands-on experience managing Azure SQL Database environments, including performance tuning, index optimization, stored procedures, query troubleshooting, database security, and operational support for application workloads. - Proficiency in Microsoft Fabric tools: Data Pipelines, Dataflows Gen2, OneLake, Notebooks.

Preferred Skills: - Experience debugging and optimizing advanced SQL queries, database objects, and legacy components. - Ability to implement database security models and data protection policies.

- Ability to implement database security models and data protection policies. - Experience using Azure SQL monitoring and tuning capabilities such as Query Store, Query Performance Insight, Database Advisor recommendations, and Azure portal metrics to identify and resolve performance bottlenecks. - Expertise in implementing row-level security, dynamic data masking, and role-based access control within Microsoft Fabric and Power BI environments.

- Design, develop, and maintain Power BI reports, dashboards, DAX expressions, KPIs, and scorecards using both Import and DirectQuery modes. - Build and orchestrate scalable ETL/ELT workflows using Fabric Data Pipelines, Dataflows Gen2, and Azure Data Factory. - Write and tune complex T-SQL and KQL queries, stored procedures, and views for performance in Synapse SQL and SQL Server environments.

- Support AI initiatives by preparing, transforming, and managing high-quality datasets for model training and inference. - Integrate AI-powered services such as Azure AI Services, Azure OpenAI, and Microsoft Fabric AI capabilities into data solutions. - Develop and maintain data pipelines that support Generative AI, predictive analytics, and machine learning workloads.

- Microsoft Certified: Fabric Data Engineer Associate (DP-700) – preferred for candidates specializing in Microsoft Fabric. - Additional Microsoft certifications such as PL-300 (Power BI Data Analyst Associate) or relevant Azure certifications are an advantage. Preferred Skills:

- Proficiency in Microsoft Fabric tools: Data Pipelines, Dataflows Gen2, OneLake, Notebooks. - Hands-on experience with Spark/PySpark and data integration from varied sources. - Microsoft Certified: Fabric Data Engineer Associate (DP-700) – preferred for candidates specializing in Microsoft Fabric.

- Hands-on experience building and maintaining OLTP databases, including relational data modeling, schema design, normalization, SQL query development, indexing, transaction handling, performance troubleshooting, and data integrity controls - Design, develop, and maintain Power BI reports, dashboards, DAX expressions, KPIs, and scorecards using both Import and DirectQuery modes. - Build and orchestrate scalable ETL/ELT workflows using Fabric Data Pipelines, Dataflows Gen2, and Azure Data Factory.

- Bachelor's or master's degree in computer science, Information Systems, or related field. - Demonstrated hands-on experience in Power BI development and data engineering, including building enterprise dashboards and semantic models, developing DAX calculations, implementing ETL/ELT pipelines, integrating multiple data sources, optimizing data models and queries, and supporting production data workloads. - Strong expertise in T-SQL and KQL, with demonstrated query optimization skills.

- Experience using Azure SQL monitoring and tuning capabilities such as Query Store, Query Performance Insight, Database Advisor recommendations, and Azure portal metrics to identify and resolve performance bottlenecks. - Expertise in implementing row-level security, dynamic data masking, and role-based access control within Microsoft Fabric and Power BI environments. - Familiarity with Microsoft One Lake architecture, including data cataloging, lineage tracking, item-level security, and workspace-based access management.