Description

• Design, develop, and maintain scalable and high-performance data pipelines using Microsoft Fabric, Azure Data Factory (ADF), Azure Synapse Analytics, and Azure Data Services.
• Lead the architecture, implementation, and optimization of enterprise data platforms and data warehouse solutions.
• Develop and optimize ETL/ELT frameworks to support large-scale data integration and transformation requirements.
• Design and implement dimensional data models, star schemas, snowflake schemas, and data marts to support business intelligence and analytics.
• Build and manage data lakehouse architectures leveraging Microsoft Fabric.
• Establish data governance, data quality, metadata management, and security best practices.
• Collaborate with business stakeholders, architects, analysts, and development teams to define and implement data strategies.
• Optimize SQL queries, stored procedures, indexing strategies, and database performance.
• Monitor, troubleshoot, and resolve complex data pipeline and platform issues.
• Implement CI/CD practices and automation for data engineering workflows.
• Mentor and guide junior and mid-level data engineers by providing technical leadership and best-practice recommendations.
• Evaluate emerging Azure and Microsoft Fabric capabilities and recommend improvements to existing data architectures.
• Support advanced analytics, AI/ML, and reporting initiatives through robust data engineering solutions.

Other Responsibilities

• Provide technical leadership and guidance across data engineering projects.
• Participate in architecture reviews, design discussions, and strategic technology planning.
• Communicate project status, risks, dependencies, and mitigation plans to leadership and stakeholders.
• Ensure adherence to organizational standards, compliance requirements, and security policies.
• Foster strong collaboration with cross-functional teams and business units.
• Support production deployments, troubleshooting, and performance optimization initiatives.

Qualifications:

• 7-10 Years

Education and Experience

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
• Master's degree preferred.
• Equivalent combination of education and relevant work experience may be considered.

Required Qualifications

• 4+ years of experience in Data Engineering, with at least 3+ years of experience working on Azure-based data platforms.
• Strong expertise in SQL, query optimization, performance tuning, indexing, partitioning, and stored procedures.
• Extensive experience with Microsoft Fabric, including Lakehouse, Data Factory, Data Warehouse, Real-Time Analytics, and Data Engineering workloads.
• Advanced experience with Azure Data Factory (ADF) and enterprise ETL/ELT development.
• Strong knowledge of Data Warehousing concepts, dimensional modeling, star/snowflake schemas, and data architecture.
• Hands-on experience with Azure Synapse Analytics, Azure SQL Database, Azure Data Lake Storage (ADLS), Azure Storage Accounts, and related Azure services.
• Strong experience with Python, PySpark, Spark SQL, or similar technologies for data transformation and processing.
• Experience implementing data governance, security, lineage, and metadata management frameworks.
• Knowledge of CI/CD pipelines, source control, and DevOps practices for data engineering.
• Strong analytical, troubleshooting, and problem-solving skills.
• Excellent communication and stakeholder management skills

Key Skills

Education

Bachelor's or Master's degrees