
Squad Lead
7 days ago
Overview
The Squad Lead will be responsible for managing and guiding a multidisciplinary team to ensure successful project delivery. This role requires a blend of team management, program leadership, project planning, and deep technical expertise. The ideal candidate will have hands-on experience in Databricks, Azure Cloud, Azure DevOps, Data Engineering, and managing large-scale data programs, particularly in pricing-related domains. Knowledge of Microsoft Fabric and experience managing large teams across multiple modules is highly preferred.
Job Responsibilities
- Lead, mentor, and motivate a cross-functional team of data scientists, analysts, and developers to deliver high-quality data and analytics solutions.
- Drive large-scale, multi-module data programs, ensuring cohesion, alignment, and delivery across different squads.
- Oversee program execution, manage interdependencies, and ensure timely delivery across modules and teams.
- Develop and manage comprehensive project and program plans, ensuring alignment with business goals, delivery timelines, and budget constraints.
- Lead and manage data projects end-to-end, from requirements gathering to deployment, focusing on advanced analytics and AI-driven solutions.
- Engage and collaborate with stakeholders to understand pricing-specific data requirements and ensure business needs are translated into technical outcomes.
- Utilize both technical and functional knowledge to bridge the gap between business users and technical teams.
- Perform business analysis, including gathering and documenting requirements, performing gap analysis, and creating technical specifications.
- Drive implementation best practices using Azure DevOps for work management, CI/CD pipelines, and version control.
- Leverage knowledge of Microsoft Fabric for developing modern analytics solutions and integrating with other Microsoft ecosystem services.
- Maintain high standards for data quality, governance, and validation through rigorous testing and documentation.
- Continuously evaluate and improve team workflows, tools, and methodologies.
- Provide technical and strategic guidance on Databricks, Azure, and Data Engineering practices to ensure team productivity and innovation
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