Key Responsibilities

• Design, develop, and maintain scalable and reliable ETL/ELT data pipelines for structured and unstructured data from multiple enterprise sources.
• Architect and optimize data ingestion, transformation, and integration workflows across cloud and on-premise systems.
• Develop and optimize complex SQL queries, stored procedures, views, functions, and data transformation logic.
• Design and maintain enterprise-grade data warehouses, data marts, dimensional models, and analytical datasets.
• Build and manage data integration workflows using Azure Data Factory, Azure Databricks, Microsoft Fabric, or similar technologies.
• Work extensively with the Microsoft Azure data ecosystem, including Azure SQL, Data Lake, Synapse Analytics, and related services.
• Implement robust data cleansing, validation, reconciliation, transformation, and quality-control processes.
• Identify and resolve performance bottlenecks across data pipelines, SQL workloads, data models, and reporting solutions.
• Design solutions for scalability, reliability, maintainability, and performance across large and complex datasets.
• Translate business and analytical requirements into efficient and scalable data architectures and technical solutions.
• Design, develop, and maintain enterprise-level Power BI dashboards, reports, and semantic models.
• Build optimized Power BI data models using appropriate relationships, hierarchies, calculated columns, KPIs, and reusable measures.
• Develop complex and efficient DAX calculations and measures to support advanced analytical requirements.
• Implement Power BI security models, including Row-Level Security (RLS) and appropriate workspace and access controls.
• Manage Power BI Service components including workspaces, gateways, scheduled refreshes, deployment pipelines, and dataset configurations.
• Monitor production pipelines and reporting environments and troubleshoot data quality, integration, refresh, performance, and production issues.
• Define and follow best practices for data engineering, Power BI development, coding standards, documentation, testing, and deployment.
• Implement and support version control and CI/CD practices for data pipelines, scripts, and BI solutions.
• Participate in technical design discussions, architecture reviews, and solution planning.
• Conduct code reviews and provide technical guidance to junior and mid-level team members.
• Collaborate closely with data engineers, BI developers, architects, analysts, product teams, and business stakeholders.
• Ensure data solutions comply with organizational standards related to security, governance, data quality, and access control.
• Create and maintain technical documentation for data architecture, pipelines, transformations, data models, and reporting solutions.

Required Skills & Experience

• 6–8 years of overall experience in Data Engineering, Business Intelligence, Data Analytics, or related areas.
• Strong hands-on experience in Power BI development and administration.
• Advanced knowledge of SQL with proven experience handling complex queries and large datasets.
• Strong experience designing and developing ETL/ELT pipelines.
• Strong understanding of data warehousing, dimensional modeling, star schema, snowflake schema, and data mart design.
• Strong hands-on experience with Azure Data Factory (ADF).
• Experience with Azure Databricks, Spark, or similar distributed data-processing platforms.
• Strong experience with Power Query and data transformation.
• Intermediate to advanced expertise in DAX, including performance optimization.
• Strong experience designing and optimizing Power BI semantic models.
• Hands-on experience implementing Row-Level Security (RLS) and managing Power BI security.
• Experience with Azure SQL, Azure Data Lake Storage, Synapse Analytics, or Microsoft Fabric.
• Strong understanding of data quality, validation, reconciliation, exception handling, and error-management frameworks.
• Experience working with data from databases, APIs, files, cloud applications, and enterprise systems.
• Experience with Git or similar version-control platforms.
• Knowledge of CI/CD, automated deployment, and release-management practices.
• Strong performance-tuning and troubleshooting skills across SQL, data pipelines, and Power BI.
• Good understanding of data security, governance, access management, and enterprise data-management principles.

Preferred Skills

• Hands-on experience with Microsoft Fabric.
• Strong working knowledge of Python, PySpark, or Spark SQL.
• Experience designing solutions for high-volume and large-scale data environments.
• Knowledge of Azure DevOps or similar CI/CD platforms.
• Experience with API-based integrations and near-real-time data processing.
• Familiarity with data orchestration, monitoring, and logging frameworks.
• Understanding of Medallion Architecture, Lakehouse Architecture, and modern data-platform concepts.
• Experience leading technical implementations or mentoring development teams.
• Exposure to Agile/Scrum delivery environments.

Leadership & Stakeholder Responsibilities

• Act as a technical SME for Power BI and data engineering initiatives.
• Work directly with stakeholders to understand reporting, analytical, and data requirements.
• Recommend appropriate technical approaches, architecture, and design patterns.
• Drive technical discussions and contribute to solution architecture decisions.
• Review technical designs and ensure solutions align with scalability, security, and maintainability standards.
• Mentor team members and support knowledge-sharing across data and BI teams.
• Identify opportunities to improve existing pipelines, reporting solutions, and development processes.