Senior Lead Analyst - Data Management and Modelling

Overview

Senior Lead Analyst, Data Management & Data Engineering, delivering the Finance Systems modernization strategy and the Data Lake/Data Warehouse roadmap by building scalable, governed data foundations, pipelines, semantic models and AI-enabled analytics.

What you'll do

• Design, develop and maintain scalable data pipelines, ingestion frameworks and transformation processes across Finance systems.
• Build modern ELT/ETL solutions using Microsoft Fabric, Snowflake, dbt and cloud-native technologies.
• Develop and improve data models that support enterprise reporting, analytics, AI and self-service.
• Make sure Finance data assets are scalable, reusable, governed and ready for AI.
• Lead the move of legacy reporting solutions onto cloud-based analytics platforms.
• Design conceptual, logical and physical data models using dimensional modeling methods such as Star Schema and Snowflake Schema.
• Develop enterprise Finance data models for FP&A, Revenue, Expense, Workforce and Financial Reporting.
• Help build semantic models with consistent business definitions, metrics, hierarchies and calculations.
• Work with business stakeholders to turn reporting and analytics needs into scalable data structures.
• Build AI-ready data foundations for Generative AI, Agentic AI, Conversational Analytics and Machine Learning.
• Work with analytics and AI teams to add Large Language Model (LLM) capabilities to Finance reporting.
• Help deliver AI-powered insights, data discovery and natural language queries.
• Use AI-assisted development practices to improve engineering productivity and data quality.
• Put data governance standards into practice, including metadata management, lineage, cataloging and security controls.
• Set up monitoring and validation processes to keep data accurate and reliable.
• Support master data and reference data management.
• Make sure work meets enterprise data policies and audit requirements.
• Gather business requirements and document data flows, processes and technical specifications.
• Work closely with Finance, Technology, Product and Analytics teams to deliver solutions.
• Lead cross-functional discussions and turn business problems into technical solutions.
• Spot issues early, suggest improvements and coordinate fixes with stakeholders.
• Mentor junior team members and promote engineering best practices.

What you'll need

• Strong experience with Microsoft Fabric, Power BI, Snowflake and dbt.
• Advanced SQL and data analysis skills.
• Experience designing and building scalable data pipelines and transformation workflows.
• Strong understanding of data warehousing, data lakes, Lakehouse architectures and dimensional modeling.
• Hands-on experience with semantic models, enterprise reporting datasets and analytics platforms.
• Skill in Python, Spark or other modern data engineering tools.
• Experience integrating data from ERP or operational systems.
• Strong analytical and problem-solving skills.
• Excellent spoken and written communication.
• Experience working directly with business stakeholders and turning their needs into technical solutions.
• Ability to handle several priorities in a fast-paced environment.
• Close attention to detail and a focus on delivering business value.

Nice to have

• Experience with Generative AI, Agentic AI frameworks, AI-powered analytics or conversational intelligence platforms.
• Knowledge of Microsoft Copilot, Azure AI Services, OpenAI or enterprise AI ecosystems.
• Experience with CI/CD pipelines, DevOps practices and Infrastructure as Code.
• Familiarity with Databricks, Azure Data Factory, Synapse or other cloud analytics platforms.
• Experience with Finance, FP&A, Revenue, Workforce, Expense or Accounting data.
• Knowledge of data governance, metadata management, data cataloging and data quality frameworks.
• Experience building enterprise semantic layers and reusable business metrics.
• Certifications in Microsoft Fabric, Power BI, Snowflake, Azure Data Engineering or AI technologies.

Details

• Location: Bangalore, Karnataka, India (Bengaluru, Karnataka).
• Hybrid work model for office-based roles; work from anywhere for up to 8 weeks per year.