Data Engineer

Data Engineer | Vantrock Intelligence | Mumbai

Build the data foundation behind an AI-native operating system for real estate. Every AI system and internal tool in the company will run on what you build.

ABOUT VANTROCK INTELLIGENCE

Vantrock Intelligence is building an AI-native operating system for the real estate asset lifecycle, spanning capital raising, land acquisition, development and leasing. We are building it AI-first from the ground up, starting inside a live real estate development fund where we solve real problems, with the ambition of turning it into a product for real asset companies everywhere. We are a small, senior, fast-moving team, and we operate like the startup we are.

THE ROLE

We are looking for a data engineer who thinks about data the way an AI-native company must. This is not a traditional data role. The heart of the job is understanding how AI systems consume data, and building the foundation that turns our raw, messy real-estate data into clean, correctly structured fuel for AI. You will sit in a small core engineering team, and every engineer in the company will build on what you build.

WHAT YOU WILL OWN

– The data foundation that every AI system and internal tool in the company runs on.

– Turning large volumes of messy, unstructured real-estate data and documents into clean, well-structured data that AI can actually use.

– Reliable, automated ingestion, so new data flows in and stays clean without manual effort.

– Bringing each area's data in, working closely with the engineers who build on your work and with the business teams who hold the data.

– Data quality, security and governance, so that what the AI reads can be trusted.

MUST-HAVE QUALIFICATIONS

– Deep, hands-on command of data pipelines, ETL/ELT, and data-lake design and management.

– A genuine understanding of how AI systems consume data. This is non-negotiable. You know how to translate existing data into the right formats for LLM and retrieval (RAG) systems, and why structure and quality make or break AI performance.

– Proven experience turning large, messy, unstructured data (documents, scans, text, mixed sources) into clean, usable form.

– Experience building a data platform other engineers depend on: clear schemas, reliable access, and the discipline to say no to duplicate data stores.

– You use AI tools every day in how you build, and you treat AI's data needs as the point of the job, not an afterthought.

– Clear communication with non-technical people, because much of the data you need sits in the heads and folders of business teams.

EXPERIENCE

Around 4 to 8 years in data engineering is typical for this seat, with strong command of modern data tooling and cloud infrastructure. We weight the data systems you have built, and how well you understand AI's data needs, over years.

NICE TO HAVE

– Vector databases, embeddings and RAG pipelines at scale.

– Document and OCR extraction.

– AI tool-integration standards.

– Ontology or knowledge-graph design.

– Proptech or fintech data.

– Multi-tenant SaaS data architecture.

WHO YOU ARE

– Future-facing and AI-forward: you use AI in how you work and are excited by building an AI-native company, not attached to old ways of working.

– Entrepreneurial and self-driven: you take initiative, set your own pace, and own outcomes end to end. You don't wait to be told.

– Rigorous and foundational: you care that the data underneath is right, because everything the AI does, and every tool every team uses, depends on it.

WHY JOIN

Own the data foundation that the entire AI platform, and every team's tools, are built on. One of the most consequential technical roles in the company.

HOW TO APPLY

Apply through LinkedIn and attach your CV. Shortlisted candidates receive a short written questionnaire before any interview.