Data Engineer – Enterprise Data & AI

Company: Marlabs

Location: Bengaluru, IN (Remote)

Type: Full-time

Remote: Yes

Posted: 2026-11-11

About this role

Marlabs, a global AI and Digital Solutions Consulting firm, delivers intelligent solutions across AI, data, analytics, and product engineering. Since 2000, we have partnered with some of the largest healthcare, life sciences, financial services, and government organizations worldwide. As we continue to expand our global footprint, we have an exciting opportunity for a highly skilled Data Engineer – Enterprise Data & AI to join our innovative and dynamic team.

**Data Engineer – Enterprise Data & AI | About You**

As a Data Engineer – Enterprise Data & AI, you will build and operate the governed data foundation that powers enterprise AI agents, analytics, and intelligent business applications. You will develop production-grade data pipelines, connectors, and retrieval layers that integrate structured and unstructured information across enterprise platforms. The ideal candidate combines strong Python, SQL, API integration, data modeling, and data governance expertise with experience integrating complex systems such as ERP, CRM, collaboration platforms, and modern enterprise data platforms.

**Data Engineer – Enterprise Data & AI | Day-to-Day**

  • Design, build, and maintain scalable data pipelines, connectors, and retrieval layers that enable secure access to structured and unstructured enterprise data for AI and analytics use cases.
  • Integrate data across enterprise platforms including ERP systems, Salesforce, SharePoint, Teams, Outlook, Palantir Foundry, and other internal and external data sources.
  • Develop and maintain data models supporting commercial and operational information such as RFQs, quotes, product specifications, BOMs, part numbers, pricing, costs, margins, contracts, customer history, complaints, and opportunities.
  • Build data ingestion, transformation, and retrieval workflows using Python, SQL, REST APIs, Spark or Polars, ensuring scalability, reliability, and production performance.
  • Implement data quality, metadata, lineage, security, a...

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