Data Engineer

Innodata Inc.; Hubli; On-site; INR 1,500,000 - 2,500,000; Full time

Job summary

Innodata Inc. seeks a seasoned GCP Data Engineer to design and build scalable data warehouses, lakes, and pipelines in a remote setting. You will enable AI-driven analytics for supply chain, real estate, and automation initiatives.

The ideal candidate will implement secure ETL/ELT processes on GCP, optimize performance, and collaborate with AI/ML teams to deliver production-ready data products.

Qualifications

• Experience designing and implementing ETL/ELT pipelines.
• Strong SQL and Python skills.
• Experience with GCP data services.
• Knowledge of data lake and data warehouse architectures.
• Familiarity with AI/ML data pipelines and RAG concepts is a plus.

Responsibilities

• Design and implement data solutions on GCP using BigQuery, Dataflow, Pub/Sub, and Looker/BI.
• Build ETL scripts from ERP, procurement, logistics, and facilities systems.
• Develop data pipelines for data lakes and warehouses.
• Create end-to-end data and BI layers (ETL, storage, transformation, visualization).
• Collaborate with supply chain and real estate teams for AI pipelines.
• Ensure data governance, lineage, and compliance.
• Optimize query performance and pipeline reliability.

Skills

GCP

SQL

Python

ETL/ELT

Data warehousing

AI pipelines

Tools

BigQuery

Dataflow

Pub/Sub

Cloud Storage

Looker/BI

Job description

Experience: 5-8 years

Work Mode: Remote

About Role :

We are seeking a GCP Data Engineer to design and build enterprise data warehouses, data lakes, and pipelines that power data-driven decision-making for data center supply chain and real estate operations. This role is responsible for creating scalable, secure, and optimized ETL infrastructure on Google Cloud Platform (GCP), while enabling advanced AI/ML use cases such as RAG, copilots, and agentic AI for predictive analytics and workflow automation.

Responsibilities:

• Design and implement data-driven solutions on GCP including BigQuery, Cloud Storage, Dataflow, Pub/Sub, and Looker/BI.
• Build ETL scripts using SQL and Python to extract, clean, and transform structured and unstructured data from ERP, procurement, logistics, and facility management systems.
• Develop and optimize data pipelines for ingestion, transformation, and loading into enterprise data lakes and warehouses.
• Build and extend end-to-end data and BI solutions, spanning extraction, storage, transformation, and visualization layers.
• Partner with supply chain, real estate, and AI/ML teams to provide pipelines for AI solutions (e.g., RAG ingestion, Copilot integration, multi-agent workflows).
• Ensure data governance, lineage, and compliance across supply chain datasets.
• Continuously optimize query performance, ETL processes, and pipeline reliability.

Skills Required:

• Strong hands-on expertise with GCP services: BigQuery, Dataflow, Pub/Sub, Cloud Storage, Looker/BI (or similar).
• Advanced proficiency in SQL (complex queries, optimization) and Python (data engineering, scripting, APIs).
• Experience building ETL/ELT pipelines operating on structured and unstructured data sources.
• Knowledge of enterprise data warehouse and data lake architectures.
• Exposure to data pipelines for AI/ML (vector DB ingestion, embeddings, RAG pipelines, copilots, agents).