Fabric Data Engineering Manager

Responsibilities

• Leading data engineering workstreams focused on Fabric-based modernization programs and cloud data platform delivery
• Managing project plans, timelines, budgets, and deliverables across multiple client engagements
• Guiding teams in the design and build of data pipelines, data lakes, and data warehouses using Azure Data Factory, Databricks, and Snowflake
• Reviewing data architecture, modeling, integration, transformation, and validation activities to support reliable analytics outcomes
• Coaching junior team members on engineering methods, code review practices, and delivery coordination
• Translating business needs into scalable data solutions and resolving design issues across source systems and target platforms
• Overseeing performance tuning, query optimization, and troubleshooting across warehouse and pipeline environments
• Applying data quality, security, anonymization, and governance practices throughout solution delivery
• Identifying opportunities to improve automation, reuse, and modern data engineering approaches across client programs
• What You Must Have
• At least a Bachelor's degree
• At least 8 years of experience
• Oral and written proficiency in English required
• Leads delivery of Microsoft Fabric solutions, defines architecture, and manages teams and client relationships.
• Define data architecture and solution design using Microsoft Fabric
• Lead large-scale data transformation and migration projects
• Oversee development of enterprise-grade data platforms
• Ensure governance, security, and compliance frameworks
• Drive performance optimization and cost management
• Manage stakeholders and translate business needs into technical solutions
• Lead and mentor teams (Associates & Senior Associates)
• Support pre-sales, proposals, and solution demos
• What Sets You Apart
• Preference for at least one of the following fields of study: Management Information Systems, Computer and Information Science, Systems Engineering, Electrical Engineering, Chemical Engineering, Industrial Engineering, Mathematics, Statistics, Mathematical Statistics
• Demonstrating data engineering leadership across client delivery workstreams
• Managing Fabric, Databricks, and Snowflake modernization initiatives
• Coaching teams through Agile delivery and feedback cycles
• Applying AWS, Azure Data Factory, and Apache Airflow
• Translating data architecture needs into scalable pipeline designs