Description

Design, build, and optimize scalable data pipelines and enterprise data platforms using Microsoft Fabric and Azure services.

This role is hybrid.

Responsibilities

• Architect and maintain data lakehouse solutions and data warehouses using Microsoft Fabric, Azure Data Factory, and Azure Synapse Analytics.
• Develop and optimize ETL/ELT frameworks, SQL queries, and stored procedures for large-scale data integration.
• Design dimensional data models, including star and snowflake schemas, to support business intelligence and analytics.
• Implement CI/CD practices, data governance, and security best practices for data engineering workflows.
• Mentor junior engineers and collaborate with stakeholders to define data strategies and resolve complex pipeline issues.

Required Skills

• 7+ years of experience in Data Engineering, with 4+ years in the role and 3+ years on Azure-based platforms.
• Expertise in Microsoft Fabric (Lakehouse, Data Factory, Data Warehouse, Real-Time Analytics).
• Strong proficiency in SQL, query optimization, indexing, partitioning, and stored procedures.
• Hands-on experience with Azure Data Factory (ADF), Azure Synapse Analytics, Azure SQL Database, and Azure Data Lake Storage (ADLS).
• Proficiency in Python, PySpark, and Spark SQL for data transformation and processing.
• Deep understanding of data warehousing concepts, dimensional modeling, and data architecture.
• Experience implementing data governance, metadata management, and lineage frameworks.
• Familiarity with CI/CD pipelines, source control, and DevOps practices for data engineering.
• Bachelor's degree in Computer Science, IT, or Engineering; Master's degree preferred.

Preferred Skills

• Experience supporting advanced analytics, AI/ML, and reporting initiatives.
• Knowledge of emerging Azure capabilities and data architecture improvements.

Key Skills

Education

Bachelor's or Master's degrees