THE ROLE: Data Engineer for Insight Globals AI Product & Services Division out of our Hyderabad location
We are looking for a Data Engineer to build the data foundation that IG Labs' agentic systems run on. Every agent we deploy into a client is only as good as the data and structure beneath it, and you are the engineer who builds that foundation: the pipelines, the models and ontologies, and the retrieval layer that feeds the agents the right context. You take on the hardest data problems in our client work: the source no one can cleanly extract, the ontology that has to capture how a business really works, the retrieval that has to surface the right context every time. You own the data foundation from a raw, messy starting point to a governed, reliable system in production, and you are accountable for whether the agents built on it can be trusted.
The pipelines, connectors, and ontology fragments you create become Factory IP that compounds across every engagement, so each project starts ahead of the last. You are a senior engineer in our delivery organization, based in India, working within the POD model alongside the Technical Architects, Forward Deployed Engineers, and the UI/UX and Technical/Field engineers who build the rest of the system.

1- Solving the Hardest Data Problems
Take on the toughest data problems in our client work: the messy, incomplete, undocumented client data that stands between an idea and a working agent.
Design the data models and ontologies the agentic system operates on: entities, relationships, states, and the business rules that govern them.
Take an open-ended data problem with no clean source and engineer a reliable, governed path to usable data.
2- Data Engineering
Build production-grade ingestion, ETL and ELT, and transformation pipelines across batch and streaming.
Own data quality, governance, and lineage, the difference between an agent you can trust and one you cannot.
Engineer for performance and cost, so the foundation scales with the client without surprises.




Own your work end to end within live client engagements, from a raw, messy data starting point to a governed system running in production.
Bring the deep data engineering expertise a client engagement depends on, as a peer to the Technical Architects, Forward Deployed Engineers, and other engineers in the POD.
4- Building Reusable Capability
Turn everything you solve into reusable capability: pipelines, connectors, ontology fragments, and data-quality frameworks that make the next engagement faster.
The data foundations you create are how the next project starts ahead of where the last one finished.
Treat capability-building as core, not overhead. You build the data foundations that production agentic systems run on, not dashboards and reports.
You build reusable, governed data capability that outlives a single engagement.
you build the data foundation the engagement is built on. 8+ years of hands-on data engineering in production, with a track record of building reliable pipelines over messy, real-world data.

- Solid with ingestion, ETL and ELT, transformation, and warehousing or lakehouse design.
- Fluent in SQL and Python. Experience building the data foundations behind ML or AI systems, including embeddings, vector stores, and retrieval. Rigorous about data quality, governance, and lineage.
- Depth with streaming, modern transformation and orchestration tooling (dbt, Spark, Airflow), and ontology or knowledge-graph design.
- Experience building retrieval for RAG and agentic systems. Experience in a consulting, professional services, or client-delivery environment.
- Familiarity with the data, access, and compliance constraints of regulated clients in financial services or healthcare.

Languages- Expert Level: SQL, Python

Snowflake, BigQuery, Databricks

Governance & Quality - Advanced Level: Data quality, lineage, cataloging

Cloud Data Platforms- Advanced Level: AWS, Azure, GCP data services

AI & Agentic- Advanced Level: RAG and retrieval for agents, embeddings pipelines, agentic data workflows

Data Architecture
Retrieval & RAG Data
Data Quality

📌 Data Engineer - ML & AI (Secunderabad)
🏢 Insight Global
📍 Secunderabad