Azure Data Engineer

Position Overview We are seeking a highly skilled Azure Data Engineer with Business Intelligence (BI) expertise and 3–6 years of industry experience. The ideal candidate will have strong hands-on development skills, experience in data engineering on Azure, BI solution design, data modeling, and the ability to collaborate with stakeholders to translate business needs into scalable data solutions. Experience in leading small teams, performing requirements gathering, and guiding solution design is essential. Key Responsibilities 1. Data Engineering & Development - Design, develop, and maintain Azure-based data pipelines using: - Azure Data Factory (ADF) - Azure Databricks / PySpark - Azure Synapse Analytics - Azure Data Lake Storage (ADLS Gen2) - Implement scalable ETL/ELT processes for ingestion, transformation, loading of structured and unstructured data and migration - Optimize data pipelines for performance, cost-efficiency, and reliability. - Develop robust data models, data marts, star/snowflake schemas for analytics and BI consumption. 2. Business Intelligence & Analytics - Design and develop BI solutions and dashboards using: - Power BI (DAX, Power Query), Tableau - Azure Analysis Services / Power BI Premium semantic models - Ensure BI solutions align with business expectations, performance standards, and visualization best practices. - Validate data accuracy, data quality, and ensure smooth reporting enablement for business stakeholders. 3. Requirements Gathering & Solutioning - Collaborate with business users, product owners, and analysts to understand reporting and analytics requirements. - Translate business needs into technical specifications, data models, and architecture. - Propose scalable, secure, and efficient Azure data solutions. - Present solution approaches and architecture options to stakeholders. 4. Team Leadership & Collaboration - Lead a small team of developers and provide technical guidance, code reviews, and mentoring. - Work closely with cross-functional teams including data scientists, BI developers, and cloud architects. - Manage task prioritization, sprint planning, and ensure timely delivery of data engineering components. 5. Data Quality, Governance & Operations - Implement best practices for data quality, validation, and monitoring. - Ensure compliance with security, governance, and data privacy standards (RBAC, encryption, data lineage). - Support production deployments, root-cause analysis, and continuous improvements. Required Skills & ExperienceTechnical Skills - Azure Data Engineering: ADF, Databricks, PySpark, Synapse, ADLS, Azure SQL, Key Vault. - Programming: SQL (advanced), PySpark/Python, T-SQL. - Data Modeling: Dimensional modeling, semantic models, DAX, star/snowflake. - BI Development: Power BI dashboards, reports, DAX calculations, Power Query. - Data Integration: API integrations, event-based ingestion, CDC, Kafka/Event Hub knowledge (nice to have). - Version control & DevOps: Git, Azure DevOps CI/CD for data pipelines (preferred). Soft Skills - Strong analytical and problem-solving abilities. - Excellent communication, ability to work with business and technology stakeholders. - Leadership qualities including task delegation, code review, and mentoring of junior engineers. - Ability to understand end-to-end data flows and architect scalable solutions. Preferred Qualifications - Microsoft Certified: Azure Data Engineer Associate (DP-203) or equivalent. - Experience working in Agile/Scrum environments. - Exposure to data warehousing concepts and cloud data architecture patterns. - Knowledge of performance tuning for SQL, BI dashboards, and big-data pipelines.