Principal Architect – AI-Native Data Analytics & MDM Platform (SAP + Multi-Source) (10 years)

Principal Architect – AI-Native Data Analytics & MDM Platform (SAP + Multi-Source) (10 years)

Experience: 10  years

Allocation: Remote

Position open: 01

Working time: IST with little flexible depends on meetings

Tenure: 6+ months

Onboarding: immediate (as per your availability)

Additional Details Require: NA

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 optimize 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

Optimize 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 harmonization 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)

Stabilize 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 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 0→1 platform evolution

Problem solvers passionate about enterprise data and intelligent automation

Also help us with below information

Total Exp-

Architect Exp-

Scale Handled-

Distributed Systems Experience-

Enterprise Data / MDM Experience-

SAP / ERP Integration Experience-

AI-Native Platform Exposure-

MongoDB / NoSQL Design-

Data Pipeline Experience-

Early Start Date-

Current location-