Live opening · Posted 2 days ago

Data & Analytics Leader

Talentmatics · Mumbai, Maharashtra, India (On-site)

Linkedin No

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At a glance

The key details from the original listing.

Posted 2 days ago

CompanyTalentmatics

LocationMumbai, Maharashtra, India (On-site)

Work modeNo

Source

Listed2 days ago

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About the role

Description supplied by the original job listing.

Our client is looking for an experienced Data & Analytics Leader with 18+ years of experience in building and scaling enterprise data & analytics practices. The role requires strong GCC experience, global stakeholder management, data modernization, architecture, governance, and GenAI exposure.
Key Responsibilities
Build, scale, and lead enterprise Data & Analytics practices.
Drive data transformation and modernization, including migration from Azure Synapse to Snowflake.
Lead transition from legacy data and visualization platforms to modern technologies.
Drive the transition from MicroStrategy to Power BI and strengthen enterprise data visualization capabilities.
Define and implement data architecture, governance, MDM, and data quality frameworks.
Lead data engineering initiatives using Azure Data Factory (ADF).
Identify and implement GenAI use cases across data and analytics functions.
Collaborate with global teams and stakeholders across multiple geographies.
Establish best practices, standards, and scalable data platforms across the organization.
Mandatory Requirements
18+ years of overall experience in Data & Analytics.
Strong experience in building and growing Data & Analytics practices.
GCC experience is mandatory; industry experience is flexible.
Mandatory hands-on/leadership experience in Azure Synapse → Snowflake transformation/migration.
Experience with MicroStrategy, Power BI, and other data visualization platforms.
Strong knowledge of Data Architecture, Data Governance, MDM, and Informatica.
Experience transitioning legacy technologies to modern/new-age data platforms.
Strong GenAI exposure and understanding of enterprise GenAI applications.
Good experience with Azure Data Factory (ADF).
Global exposure is mandatory, with experience working with teams across geographies

Work arrangement
No

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