Technical Architect - Data Product Manager

Mphasis; Bengaluru; On-site; INR 3,000,000 - 5,500,000; Full time

Job summary

Mphasis in Bengaluru is seeking a Data Product Manager for the Enterprise Data Platform to own vision, strategy, roadmap, governance, and adoption of trusted, AI-ready data products powering applications and analytics.

You will lead data platform modernization across data lake, governance, MDM, APIs, and enterprise integration, collaborating with business, engineering and security teams to maximize value and ensure a single source of truth.

Qualifications

• 10+ years in Data, Analytics, or Data Architecture.
• Proven leadership of Enterprise Data Platforms and Data Governance programs.
• Experience with Data Lakes, APIs, and governance initiatives.
• Strong executive stakeholder management and cross-functional leadership.

Responsibilities

• Define and own the Enterprise Data Platform strategy, roadmap, and outcomes.
• Build enterprise data products across Data Platform, Data Lake, Analytics, AI.
• Translate business requirements into scalable, governed data capabilities.
• Drive onboarding of applications and data assets onto the platform.
• Establish data quality, metadata, lineage, MDM, security and access controls.
• Lead API-first, event-driven, and batch integration strategies.

Skills

Data Platforms

Data Lakes

Data Governance

MDM

API Integrations

Stakeholder Mgmt

Job description

Data Product Manager – Enterprise Data Platform

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

• Define and own the Enterprise Data Platform and Data Product strategy, roadmap, and business outcomes.
• Build and manage enterprise data products across Data Platform, Data Lake, Analytics, AI, and Integration domains.
• Translate business requirements into scalable, governed, and reusable data capabilities and services.
• Drive onboarding of enterprise applications, data domains, and data assets onto the platform.
• Establish and govern Data Quality, Metadata, Lineage, Master Data Management (MDM), Security, and Access Controls.
• Lead platform modernization, cloud-native data initiatives, self-service analytics, and AI-ready data programs.
• Partner with Business, Engineering, Architecture, Security, and Analytics teams to maximize platform adoption and business value.
• Define KPIs, SLAs, adoption metrics, and value realization for enterprise data products.
• Drive investment decisions, stakeholder engagement, and enterprise-wide data strategy.
• Build a team to manage the data platform
• Lead API-first, event-driven, batch, and real-time enterprise integration strategies.
• Design and govern seamless data flows across multiple SaaS, cloud, and enterprise applications.
• Ensure high-quality, low-latency, and reliable data movement without data loss or operational disruption.
• Drive Data Lake architectures supporting complex transformations, enrichment, validation, reconciliation, and cross-reference processing.
• Establish standards for API integrations, CDC, event streaming, data synchronization, and data harmonization.
• Implement and govern Golden Record and Master Data Management (MDM) frameworks to maintain a single source of truth across enterprise systems.
• Ensure all enterprise data products comply with governance, quality, security, privacy, and audit requirements.

Platform Ownership & Expertise

Strong understanding of enterprise-scale Data Platforms, including:

• Data Integration, Pipelines, Automation, APIs, CDC, and Event Streaming
• Data Lake, Data Catalog, Metadata, Lineage, and Master Data Management (MDM)
• Golden Record Architecture, Data Quality, Data Governance, and Security
• AI, Copilot, Knowledge Management, and Intelligent Automation
• Enterprise Search, Analytics, and Self-Service Data Products
• RBAC, Identity Management, Compliance, and Audit Controls
• Platform Operations, Monitoring, Release Management, and Reliability Engineering

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

• 10+ years of experience in Data, Analytics, Data Engineering, Data Architecture, Enterprise Integration, or Digital Transformation.
• 5+ years leading Enterprise Data Platforms, Data Products, Data Governance, or Data Management programs.
• Proven experience with Data Platforms, Data Lakes, API-based integrations, Analytics, and Governance initiatives.
• Strong experience managing large-scale enterprise integrations involving multiple SaaS applications and business-critical data flows.
• Demonstrated expertise in Master Data Management, Golden Record architecture, and enterprise data governance.
• Strong executive stakeholder management and cross-functional leadership skills.

Preferred Certifications

• Certified Scrum Product Owner (CSPO) or SAFe Product Manager
• Certified Data Management Professional (CDMP)
• Microsoft Fabric Analytics Engineer Associate
• Azure Solutions Architect Expert

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.