Technical Architect - Data Product Manager
Mphasis · IT Services & Consulting
- Bangalore, India
- On-site
- Posted yesterday
- Product Management
About the job
JD – Data Product Manager
Data Product Manager – Enterprise Data Platform
Role Purpose
Own the vision, strategy, roadmap, governance, and adoption of the Enterprise Data Platform, enabling trusted, secure, reusable, and AI-ready data products that power business applications, analytics, automation, and digital transformation.
Act as the single point of accountability for Data Platform, Data Lake, Data Governance, Data Products, AI Enablement, API Management, and Enterprise Data Architecture, ensuring enterprise data is managed as a strategic business asset.
Key Responsibilities
Enterprise Integration & Data Architecture
Platform Ownership & Expertise
Strong understanding of enterprise-scale Data Platforms, including:
Must possess hands-on experience designing real-time and batch data flows across multiple SaaS and enterprise applications, implementing complex transformations, validations, lookups, cross-reference rules, and maintaining a single source of truth through governed Golden Record and Master Data architectures.
Required Experience
Preferred Technologies
Azure Data Factory • Databricks • ADLS Gen2 • SQL Server • Oracle • MongoDB • Snowflake • AWS Data Services • Kafka • APIs • CDC • MDM • Data Governance & Catalog Platforms
Preferred Certifications
Key Skills
Data Product Management • Enterprise Data Platform • Data Lake • Enterprise Integration • API Management • Real-Time Data Architecture • Golden Record Management • Master Data Management • Data Governance • Data Quality • Metadata & Lineage • AI Enablement • Data Architecture • Cloud Data Platforms • Analytics • Stakeholder Management • Enterprise Transformation
Success Profile
A strategic leader who treats data as a product and combines the capabilities of a Data Product Manager, Enterprise Data Architect, Integration Architect, Data Governance Leader, and Platform Owner .
Responsible for delivering trusted, governed, real-time, AI-ready, and reusable enterprise data products while enabling seamless integration across multiple SaaS applications, enterprise systems, Data Lakes, AI platforms, and business applications through a single source of truth built on Golden Record and Master Data Management principles.