Timezone: IST, with a little flexible depends on meetings

We are an AI-native Data Analytics & Master Data Management (MDM) platform designed for modern enterprises. Our platform unifies master data across systems like SAP, HubSpot, SAGE, Excel, and other enterprise sources, while enabling AI-first data governance, data quality automation, and intelligent data fixing at scale.

We are reimagining how enterprises manage master data — shifting from manual, rule-heavy systems to AI-first, autonomous data platforms that can ingest, cleanse, govern, and optimise millions of records with minimal human intervention.

About the Role

We are looking for a hands-on Principal Architect to lead the architecture and scaling of our AI-first Data Analytics Platform (DAP). This is a high-impact role where you will design and evolve a next-generation, AI-native MDM and Data Governance system that operates across multiple enterprise data sources, with SAP master data as a core focus.

You will work on a platform that:

• Imports data from SAP, HubSpot, SAGE, Excel, and other systems

• Applies AI-native data quality and governance workflows

• Enables AI-assisted data fixing and automation

• Exports governed and enriched data back to enterprise systems

This role requires deep architectural thinking, strong execution, and the ability to transform a scaling constraint solution into a robust, AI-first enterprise platform.

What You’ll Do

Architect an AI-First Data Platform

• Design and evolve an AI-native MDM and Data Governance architecture

• Build scalable systems for intelligent data ingestion, processing, and export

• Define AI-assisted workflows for data cleansing, deduplication, and golden record creation

• Architect AI copilots and automation layers for enterprise data operations

Drive Platform Scalability & Reliability

• Re-architect existing systems to handle millions of master data records

• Identify and fix performance bottlenecks, architectural debt, and scaling issues

• Design high-availability, fault-tolerant, and horizontally scalable systems

• Optimise backend services, metadata layers, and data processing pipelines

Own Enterprise Data Integrations

• Architect robust connectors for SAP and other enterprise systems

• Enable cross-platform master data harmonisation and governance

• Design schema mapping, data lineage, and auditability frameworks

• Ensure secure, compliant, and resilient data exchange pipelines

Lead AI-Native Innovation

• Embed AI-first thinking into every layer of the platform

• Design intelligent rule engines augmented with AI decisioning

• Enable natural-language-driven data operations and automation

• Build architecture for AI agents interacting with structured enterprise data

Provide Technical Leadership

• Define long-term architectural vision and technical roadmap

• Conduct design reviews and enforce engineering best practices

• Mentor senior engineers and raise the engineering bar

• Collaborate closely with product, data, and enterprise stakeholders

Required Qualifications

• 10 years of experience in backend or platform architecture

• Proven experience designing large-scale, data-intensive systems

• Strong expertise in distributed systems and scalable architectures

• Hands-on experience with Java-based backend systems

• Experience with NoSQL databases such as MongoDB (or similar)

• Strong understanding of data pipelines, ETL, and data processing systems

• Experience handling high-volume datasets (millions of records)

What Makes This Role Unique

• Build a truly AI-native MDM and Data Governance platform (not a legacy rule-only system)

• Solve complex enterprise-scale data problems across multiple source systems

• High ownership and architectural decision-making authority

• Opportunity to design AI-first data workflows from the ground up

• Work on real-world enterprise datasets, not experimental prototypes

What Success Looks Like (First 6 Months)

• Stabilise and re-architect key parts of the existing platform

• Deliver a scalable AI-first architecture blueprint

• Improve performance, reliability, and data processing scalability

• Establish robust SAP and multi-source data integration patterns

• Embed AI-native automation into core data governance workflows

Our Tech Context (Current & Evolving)

• Backend: Java-based services

• Metadata Store: MongoDB

• AI: Vupi (more would be shared during the interview)

• Integrations: SAP, HubSpot, SAGE, Excel, APIs

• Focus: AI-native automation, data governance, data quality, MDM at scale

Who Will Thrive Here

• Architects who enjoy fixing complex, real-world systems

• Builders who think AI-first, not AI as an afterthought

• Engineers who like high ownership and 01 platform evolution

• Problem solvers passionate about enterprise data and intelligent automation