Data Platform Architect

Role: Founding Data Platform Architect

Function: Data Engineering & ML Infrastructure

Salary: 70 - 100 LPA + ESOPs

About the Company:

A venture-backed, stealth-stage technology company building next-gen matchmaking and relationship platforms is hiring their founding AI/ML & Data Engineering Team.

They are on a mission to reimagine how people connect, using AI, community, and content as the building blocks. They’re not building just another dating app — they’re creating an experience where users feel: “This app gets me.”

At the core of the product are real-time, ML recommendation engines — similar to Spotify for song moods or TikTok for discovery.

They are well funded and backed by marquee VCs in India and US.

Company Philosophy:

Core belief:

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

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

Position Overview:

They are looking for a Founding Data Platform Architect to design, build, and scale the data platform and infrastructure that powers their core recommendation systems and personalization engines.

This is a 0→10 phase role — your architectural decisions and early hires will shape how the 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 the company grows. You'll work hand-in-hand with the 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 role offers:

• 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 the data + ML infra, hire the next engineers, and scale with us to millions of users
• Competitive Salary with significant ESOPs and wealth creation opportunity