Lead Data Engineer

Job Description:
Our Client is seeking a Lead Data Engineer to help drive the standardization and modernization of its enterprise data platform as the organization continues to scale its analytics capabilities. This role combines hands-on technical architecture with leadership responsibilities, with approximately 60% focused on designing and building scalable data platform architecture and 40% focused on guiding engineering standards, mentoring team members, and influencing enterprise data strategy. The Lead Data Engineer will play a key role in advancing the Client’s transition from Azure Synapse to Microsoft Fabric while ensuring the organization’s data infrastructure is governed, scalable, and aligned with long-term analytics and business objectives.

Requirements:
• 10+ years of hands-on experience in data engineering, data warehousing, and Azure cloud data platforms using Python, SQL, and ETL packages for BI Applications.
o 5+ years’ experience driving projects to delivery, and providing technical oversight, code reviews, and architectural guidance.
• 5+ years of experience architecting Azure-based data platforms (ex: Databricks, Snowflake, or Fabric).
• Expert level understanding of Medallion architecture, and data design pattern organizing data in a lakehouse into 3 progressive layers: Bronze, Silver, Gold
• Proven experience partnering with stakeholders to gather business requirements and effectively communicate technical concepts to technical and non-technical audiences.

Nice to have:
• Design, build, and lead cloud-native data architectures within Fabric
• Experience with Data modeling concepts
• Prior professional experience with regulated industry is highly preferred

Responsibilities:
• Lead design of advanced data warehouses, data lake house, and hybrid architectures.
• Drive adoption of best practices in automation, DevOps, and CI/CD for data systems.
• Evaluate and implement emerging technologies (AI/ML integration, advanced analytics).
• Partner with executives and stakeholders to align data infrastructure with business strategy.
• Design and develop complex data pipelines within Azure-based data platforms.
• Serve as a subject matter expert and mentor across the organization.
• Guide cloud resource planning, cost optimization, and capacity management.
• Troubleshoot higher-level cloud issues and coordinate with vendors or internal teams.
• Collaborate with DevOps, Security, and Product teams on cloud roadmaps.
• Define enterprise-level data architecture and infrastructure strategy.
• Troubleshoot higher-level cloud issues and coordinate with vendors and internal teams