Data Engineer

3 days ago


Indore, Madhya Pradesh, India AgileEngine Full time ₹ 12,00,000 - ₹ 24,00,000 per year


**Data Engineer - WFH

THIS IS FULLY REMOTE WORKING OPPORTUNITY**
We someone who can join in less than 15 days .

If you are interested and fulfill the below mentioned criteria then please share below information below.

  1. EMAIL ID

  2. Years of relevant experience

  3. CCTC/ECTC

  4. Notice period

  5. Updated resume mentioning all the listed skills. Also, experience in financial domain is a huge plus so if you have that experience then mention that as well in the resume

Role Overview
:

We are looking for a highly skilled Data Engineer to join MSCI and support data-driven products, AI/ML initiatives, and large-scale cloud-based systems. The role involves building robust data pipelines, optimizing data workflows, and collaborating with modelling, engineering, and product teams.

Key Responsibilities
Design, build, and maintain scalable data pipelines on GCP and Azure.

Develop and optimize ETL/ELT processes using Python.

Work closely with AI/ML teams to operationalize ML models, GenAI components, and model exposure workflows.

Implement and manage data storage solutions across SQL and NoSQL databases.

Build containerized deployments using Docker/Kubernetes.

Ensure data quality, reliability, and governance across pipelines.

Collaborate with frontend teams using React-based UIs for end-to-end solution delivery.

Monitor, troubleshoot, and enhance production data workflows.

Required Skills & Experience
Strong experience with GCP or Azure cloud data services.

Proficiency in Python for data engineering and automation.

Hands-on experience with SQL & NoSQL data stores.

Experience deploying workloads in containerized environments (Docker/K8s).

Understanding of AI/ML pipelines and model integration.

Experience with CI/CD and cloud-native DevOps practices.

Preferred Qualifications
Familiarity with GenAI tools/models.

Knowledge of React to collaborate effectively with UI development teams.

Background in financial datasets or risk analytics (a plus).

Strong problem-solving and communication skills.


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