Title: Expert Data Engineer
Shift: 11:00AM - 8:00PM
Work Mode: Hybrid
Location: Bangalore
Introduction to the job:
The AI Data Engineering Lead owns the design, build, governance, and operational
readiness of the data pipelines, data products, knowledge assets, and
retrieval-ready datasets required to power AI-enabled products.
This role ensures that AI products are not built on fragmented, low-quality,
ungoverned, or inaccessible data. The AI Data Engineering Lead works across
product, data architecture, AI engineering, platform engineering, security,
risk, compliance, MLOps/LLMOps, and operations to ensure that AI products use
trusted, permissioned, explainable, and reusable data and knowledge assets.
Some of the things you’ll be doing
1. Own AI-ready data engineering
The AI Data Engineering Lead is accountable for engineering data assets that AI
products can safely and effectively use.
* Translate AI product needs into data requirements, data pipelines, data
products, and knowledge asset requirements.
* Build and manage data pipelines that support AI-enabled applications, RAG
solutions, agents, analytics, automation, and decision-support capabilities.
* Ensure data used by AI products is complete, accurate, timely, traceable, and
fit for purpose.
* Create reusable data products that can serve multiple products, business
units, and AI use cases.
* Partner with product owners and AI engineers to define what data is required
for prompts, retrieval, grounding, classification, extraction,
recommendations, and workflow automation.
* Ensure AI data assets are engineered for scale, resilience, security, cost
efficiency, and production support.
2. Build trusted data products
The role turns raw data into governed, reusable, product-ready data assets.
* Define and build data products for key domains such as client, entity,
product, service, transaction, finance, risk, vendor, employee, jurisdiction,
and reference data.
* Establish explicit data product ownership,
📌 Expert Data Engineer (Bengaluru)
🏢 CSC
📍 Bengaluru