Lead BI Analyst

Victoria's Secret; Bengaluru; On-site; INR 1,800,000 - 3,000,000; Full time

Job summary

Victoria's Secret & Co. in Bengaluru seeks a Lead BI Analyst to own analytics strategy for Supply Chain operations. You will architect scalable data pipelines, dashboards, and governance to enable data-driven decisions across production, sourcing, and planning.

You will partner with Finance, IT, MP&A, and Merchandising to standardize metrics and deliver executive-ready reporting. The role blends hands-on development with strategic leadership and mentoring.

Responsibilities

• Architect, oversee and build scalable data pipelines and data models in Snowflake.
• Ensure best practices in performance, modularity, and maintainability.
• Design, build, and deploy data cubes, semantic layers, and project tables to support analytics.
• Design and maintain data models (conceptual, logical, physical) for reporting and analytics.
• Partner with stakeholders to translate end-use requirements into scalable data structures.
• Collaborate with analytics teams to align KPIs and data definitions.
• Serve as domain data expert for Supply Chain initiatives and advise on data assets for performance.
• Customize visualizations to drive insights and adoption.
• Improve the Supply Chain Digital Twin with IT and Data Teams.
• Ensure data assets are performant and scalable.
• Recommend new data technologies to enhance platform capabilities.
• Champion data governance for Supply Chain, curate datasets and promote trusted content.
• Identify and resolve data quality issues with root-cause analysis.
• Establish monitoring and governance for healthy analytics.
• Identify tech opportunities with product managers to drive competitive advantage.
• Own the design, delivery and governance of executive dashboards and reporting frameworks.
• Build lightweight apps using Sigma, Salesforce, Power Automate and Python.
• Develop supply chain models including forecasts and optimization or ML models.
• Lead cross-team engineering initiatives; identify architectural risks and bottlenecks.
• Identify bottlenecks and drive automation with data-driven insights.
• Experiment with new technologies to address business challenges.
• Mentor analysts and strengthen analytics capabilities.

Job description

Job Title: Lead BI Analyst

Role Overview

The Lead BI Analyst is responsible for driving the overall analytics strategy for Supply Chain Operations. This role owns the design and development of scalable tools, data models, governance frameworks, and reporting ecosystems while ensuring alignment with business goals. This role works closely with Business, Supply Chain, cross functional partners such as MP&A, Finance, Merchandising and IT teams. The individual acts as a bridge between business and technology, leading cross-functional initiatives, standardizing data management, and enabling data-driven decision-making across production, sourcing, and planning functions. This individual leverages cutting edge and proven technology to envision and develop tools and analytics that drive quantitative and qualitative business impact leveraging their deep business knowledge and technology experience. This role acts as an “Owner & Enabler”, setting direction, ensuring quality, and building long-term analytics capabilities as well as hands on development.

Core Responsibilities (Day-to-Day)

• Data Modeling & Semantic Layer Development:
  • Architect, oversee and build scalable data pipelines and data models in Snowflake.
  • Ensure best practices in performance, modularity, and maintainability.
  • Design, build, and deploy data cubes, semantic layers, and project tables within the Supply Chain MicroStrategy and other environments to support analytics, reporting, and advanced modeling use cases.
  • Design and maintain conceptual, logical, and physical data models based on business reporting and analytical requirements.
  • Partner with business stakeholders and analytics teams to understand end‑use requirements and translate them into scalable data structures.
• Analytics Enablement & Business Partnership:
  • Collaborate with operational and business analytics teams to align on standard metrics, KPIs, and data definitions, ensuring consistency across the enterprise.
  • Serve as the domain data expert for Supply Chain initiatives, providing guidance on data design, sourcing, and interpretation for projects impacting the flow of goods.
  • Act as a trusted advisor to analytics and modeling teams, ensuring data assets are fit for purpose and optimized for performance.
  • Customizes visualizations and user interface that drive insights from data and increase user adoption, speed to value and efficiency
• Supply Chain Digital Twin & Data Platform Ownership:
  • Drive continuous improvement of the Supply Chain Digital Twin, in partnership with IT and Enterprise Data Teams.
  • Ensure data assets are performant, scalable, and aligned with evolving business needs.
  • Evaluate and recommend new data technologies, tools, and architectural patterns to enhance data platform capabilities.
• Data Quality & Governance:
  • Champion the data governance program for the Supply Chain domain, including:
    • Vetting and defining curated datasets
    • Promoting trusted content within the enterprise data catalog
    • Enforcing data standards and best practices
  • Proactively identify, troubleshoot, and resolve data quality issues through root cause analysis and corrective action plans.
  • Establish monitoring frameworks, and governance processes to ensure systems are healthy and analytics are up‑to‑date.
• Domain Expertise: Identifies ways for technology, working with the business and product managers, to drive competitive advantage within the domains they support. Understands business strategy and works with product managers to co‑develop technology roadmaps. Stays abreast of industry changes.
• Analytics & Reporting: Own the design, delivery and governance of executive ready dashboards and reporting frameworks that translate findings into actional insights. Ensure consistency, scalability, and alignment of KPIs across business functions.
• Business Application Development:
  • Leverage low-code tools such as Sigma, Salesforce, Power Automate and Python to build lightweight applications that improve internal workflows and reduce manual effort.
  • Develop supply chain models such as forecasts, linear programming optimization or machine learning models
  • Lead cross-team engineering initiatives, proactively identifying architectural risks, system bottlenecks, and scalability constraints.
  • Ability to analyze bottlenecks and drive workflow automation and process optimization using data-driven insights.
• Innovation: Experiments with new cutting‑edge technologies to understand application to business challenges. Stays current with technology innovation.
• Team Mentorship & Capability Building: Mentor junior and senior analysts, define best practices, and strengthen analytics capabilities within the team.