Data Engineer

Role:

Function:

Compensation:

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:

We are looking for a Data Engineer to help design, build, and scale the data platform and infrastructure that powers our core recommendation systems and personalisation engines.

You’ll be a founding data engineer helping us lay the pipelines and infrastructure that feed our recommendation systems, onboarding flows, engagement metrics, dashboards, and ML models. You'll work hand-in-hand with our ML team to build data adapters and interfaces for model training, serving, and experimentation.

Role & Responsibilities:

• Build and scale ETL from raw app events to ML-ready features
• Build real-time and batch pipelines for user actions and events
• Contribute to the feature store, embedding pipelines, data validation, and freshness monitoring systems
• Design data layers for use in A/B tests, product metrics, and ML training
• Partner with ML engineers to deliver data adapters for model inputs, embedding generation, and training loops
• Help evolve the core event schema and data model with privacy, observability, and performance in mind

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: 3–6 years building scalable data systems in fast-moving environments.
• Industry Fit: Experience supporting RecSys, ML, or content feeds in social or consumer platforms.
• ML/RecSys Awareness: Understands how features feed into models, or has worked closely with ML teams before.
• 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 personalisation systems, recommender pipelines, or ranking models
• Exposure to A/B testing platforms or online experimentation infrastructure
• Passion for consumer social or dating products

What the role offers:

• Join a founding data team where your work is core to product experience
• Shape key decisions for a platform that will directly impact how people form meaningful relationships
• Significant ESOPs and wealth creation with market competitive cash compensation