Description

Own the architecture, development, and optimization of enterprise-scale data pipelines and lakehouse solutions on Microsoft Fabric and Azure.

This role is hybrid.

Responsibilities

• Design and implement scalable ETL/ELT frameworks using Microsoft Fabric, Azure Data Factory, and Azure Synapse Analytics.
• Build and manage data lakehouse architectures, dimensional data models, star/snowflake schemas, and data marts.
• Optimize SQL queries, stored procedures, indexing strategies, and database performance for large-scale data integration.
• Establish data governance, quality, metadata management, and security best practices across the platform.
• Implement CI/CD pipelines and automation for data engineering workflows while mentoring junior engineers.

Required Skills

• 7+ years of total experience, including 4+ years in Data Engineering and 3+ years on Azure-based platforms.
• Expertise in Microsoft Fabric workloads: Lakehouse, Data Factory, Data Warehouse, and Real-Time Analytics.
• Strong proficiency in Python, PySpark, and Spark SQL for data transformation and processing.
• Advanced SQL skills, including query optimization, performance tuning, partitioning, and stored procedures.
• Hands-on experience with Azure Synapse Analytics, Azure SQL Database, and Azure Data Lake Storage (ADLS).
• Deep understanding of data warehousing concepts, dimensional modeling, and data architecture.
• Experience implementing data governance, security, lineage, and metadata management frameworks.
• Knowledge of CI/CD pipelines, source control, and DevOps practices for data engineering.

Preferred Skills

• Master's degree in Computer Science, Information Technology, or a related engineering field.
• Experience supporting advanced analytics, AI/ML, and reporting initiatives.

Key Skills

Education

Bachelor's or Master's degrees