Senior Lead Analysts - Data Management and Modeling

IND002 Thomson Reuters International Services Private Limited; Bengaluru; Hybrid; INR 3,000,000 - 4,500,000; Full time

Benefits offered by this job

Hybrid work model

Headspace app

Flexible vacation

Mental Health Days

Retirement savings

Tuition reimbursement

Job summary

Thomson Reuters India seeks a Senior Lead Analyst, Data Management & Data Engineering in Bengaluru. You will design and build scalable data foundations, data pipelines and semantic models to support Finance reporting, AI and self-service analytics.

The role requires strong SQL, Python/Spark skills and experience with Fabric, Snowflake and dbt in a modern data stack. Hybrid work is offered with cross-functional collaboration across Finance, Technology and Analytics.

Qualifications

• 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.

Responsibilities

• Design, develop and maintain scalable data pipelines and transformation processes across Finance systems.
• Build 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.

Skills

Microsoft Fabric

Power BI

Snowflake

dbt

SQL

Data pipelines

Dimensional modeling

Python

Spark

ERP data integration

Stakeholder communication

Problem solving

Tools

Databricks

Azure Data Factory

Synapse

CI/CD pipelines

Job description

Job Description

Our Data & Analytics team builds trusted, scalable, AI-ready data platforms that help people make decisions across our global organization. We're modernizing reporting, analytics, data management and AI with modern cloud technologies, semantic models and intelligent data products. As Senior Lead Analyst, Data Management & Data Engineering, you'll play a key part in delivering our Finance Systems modernization strategy and our Data Lake/Data Warehouse roadmap. You'll design and build scalable data foundations, modern data pipelines, governed semantic models and AI-enabled analytics. Your work will help the business get insights faster and make self-service analytics easier.

Key Responsibilities

• 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.

Required Qualifications

• 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

Preferred Qualifications

• 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.

What’s in it For You?

Hybrid Work Model

We’ve adopted a flexible hybrid working environment (2-3 days a week in the office depending on the role) for our office-based roles while delivering a seamless experience that is digitally and physically connected.

Flexibility & Work-Life Balance

Flex My Way is a set of supportive workplace policies designed to help manage personal and professional responsibilities, whether caring for family, giving back to the community, or finding time to refresh and reset. This builds upon our flexible work arrangements, including work from anywhere for up to 8 weeks per year, empowering employees to achieve a better work-life balance.

Career Development and Growth

By fostering a culture of continuous learning and skill development, we prepare our talent to tackle tomorrow’s challenges and deliver real-world solutions. Our Grow My Way programming and skills-first approach ensures you have the tools and knowledge to grow, lead, and thrive in an AI-enabled future.

Industry Competitive Benefits

We offer comprehensive benefit plans to include flexible vacation, two company-wide Mental Health Days off, access to the Headspace app, retirement savings, tuition reimbursement, employee incentive programs, and resources for mental, physical, and financial wellbeing.

Culture

Globally recognized, award-winning reputation for inclusion and belonging, flexibility, work-life balance, and more. We live by our values: Obsess over our Customers, Compete to Win, Challenge (Y)our Thinking, Act Fast / Learn Fast, and Stronger Together.

Social Impact

Make an impact in your community with our Social Impact Institute. We offer employees two paid volunteer days off annually and opportunities to get involved with pro-bono consulting projects and Environmental, Social, and Governance (ESG) initiatives.

Making a Real-World Impact

We are one of the few companies globally that helps its customers pursue justice, truth, and transparency. Together, with the professionals and institutions we serve, we help uphold the rule of law, turn the wheels of commerce, catch bad actors, report the facts, and provide trusted, unbiased information to people all over the world.

About Us

Thomson Reuters informs the way forward by bringing together the trusted content and technology that people and organizations need to make the right decisions. We serve professionals across legal, tax, accounting, compliance, government, and media. Our products combine highly specialized software and insights to empower professionals with the data, intelligence, and solutions needed to make informed decisions, and to help institutions in their pursuit of justice, truth, and transparency. Reuters, part of Thomson Reuters, is a world leading provider of trusted journalism and news. We are powered by the talents of 26,000 employees across more than 70 countries, where everyone has a chance to contribute and grow professionally in flexible work environments. At a time when objectivity, accuracy, fairness, and transparency are under attack, we consider it our duty to pursue them.

To ensure we can do that, we seek talented, qualified employees in all our operations around the world regardless of race, color, sex/gender, including pregnancy, gender identity and expression, national origin, religion, sexual orientation, disability, age, marital status, citizen status, veteran status or any other protected classification under applicable law.

Thomson Reuters is proud to be an Equal Employment Opportunity Employer providing a drug-free workplace.

We also make reasonable accommodations for qualified individuals with disabilities and for sincerely held religious beliefs in accordance with applicable law.

More information on requesting an accommodation here.

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