Founding Data Platform Architect

Role: Founding Data Platform Architect

Function: Founding Data Engineering and ML Infrastructure

Location: Gurgaon

Type: Full-time

Salary: 50-80+ LPA + ESOPs

About the Company:

An early-stage, US-based venture-backed technology company focused on creating innovative platforms for building meaningful relationships. They aim to transform how people connect by harnessing artificial intelligence, fostering community engagement, and delivering tailored content.

Rather than developing another conventional social app, they’re crafting a unique experience that resonates deeply with users, making them feel truly understood. Central to our platform is a dynamic, machine-learning-powered recommendation system, drawing inspiration from the personalised discovery engines of leading music and video platforms.

With strong financial backing from top-tier venture capital firms in India and the United States, they are well-positioned to advance our mission with innovation and impact.

Company Philosophy:

They believe:

• Great data + Good models = Great recommendations
• Good data + Great models = Average recommendations

That’s why they’re investing in data infrastructure from our inception and foundation.

Position Overview:

We are looking for a Founding Data Platform Architect to design, build, and scale the data

platform and infrastructure that powers our core recommendation systems and personalization engines. 

This is a 0→10 phase role — your architectural decisions and early hires will shape how our product thinks, recommends, and adapts.

You'll also play a player-coach role: contributing directly to code and architecture while hiring and leading a small team of data engineers as we grow. You'll work hand-in-hand with our ML team to build data adapters and interfaces for model training, serving, and experimentation.

Role & Responsibilities:

• Architect the entire data platform from scratch — including event capture, batch and streaming pipelines, and feature engineering
• Build the foundational event streams that capture swipes, likes, video views, and profile interactions
• Design and implement a feature store and embedding pipeline to power matchmaking, feed ranking, and personalisation
• Collaborate with ML engineers to support data adapters, model input schemas, and real-time scoring interfaces
• Define standards for data quality, governance, freshness, observability, and security across teams
• Own the strategy for tools, schemas, governance, scalability, and future-proofing as models evolve
• Recruit, mentor, and lead a small team of data engineers and analysts over time

Ideal Profile:

You’re a systems thinker who starts with data and designs for scale. You’ve likely been at

early-stage or high-scale consumer platforms — social, gaming, transactions, or media.

• Experience: 6–12 years building scalable data systems in fast-moving environments.
• Industry Fit: Experience supporting RecSys, ML, or content feeds in social or consumer platforms.
• Architecture Skills: Designed systems spanning batch + streaming, raw → clean → features → serving.
• Leadership: Ability to mentor junior engineers or build small teams from scratch.
• ML Awareness: Worked closely with ML teams; understands feature engineering, embedding stores, retrieval systems, and typical models.
• Product Empathy: Understands how data impacts user experience, not just analytics.
• Tools Fluency: Proficient in Kafka, Spark, Flink, Airflow, dbt, Redis, BigQuery, Feast, Terraform; can pick the best tool for the job.

Nice to have:

• Experience with graph modelling for users/interactions
• Familiarity with privacy-aware infrastructure (GDPR, PII, consent)
• Exposure to A/B testing platforms or online experimentation infrastructure

What we offer: 

• You’ll be the first data architect at a company where recommendation is the product
• Your platform will directly impact how people form meaningful relationships
• You’ll shape our data + ML infra, hire the next engineers, and scale with us to millions of users
• Significant ESOPs and wealth creation with market-competitive cash compensation