Azure Data Engineer

Wipro; Hyderabad; Hybrid; INR 2,800,000 - 4,000,000; Full time

Job summary

Wipro is seeking an Azure Data Engineer (Lead and Senior) to design and implement enterprise data solutions from Hyderabad. You will architect data models, manage data pipelines, and collaborate with cross-functional teams to ensure scalable, secure data platforms.

The role requires 6–11 years of experience, strong Python/SQL skills, and hands-on cloud data services (Azure/AWS/GCP) with governance and DataOps focus. Lead mentorship and ensure quality throughout the data lifecycle.

Qualifications

• Must have strong background in enterprise data architecture, data modeling and data governance.
• Proficient in Python, SQL, ETL/ELT and API automation with code quality practices.
• Hands-on experience with cloud data platforms (Azure/AWS/GCP) and modern data warehouses.
• Knowledge of data quality, lineage, metadata, privacy and security.
• Experience with DataOps, DevSecOps and CI/CD pipelines; mentoring others.

Responsibilities

• Lead data architecture and solution design for data platforms (DW, lakehouse, data catalog).
• Develop end-to-end data pipelines with reliable monitoring and observability.
• Collaborate with stakeholders to ensure scalable and compliant data solutions.

Skills

Enterprise data architecture

Python

SQL

ETL/ELT

APIs

Automation

Testing

Code review

Troubleshooting

Performance tuning

Stakeholder management

Technical mentoring

AI/ML data foundations

RAG

Vector search

MLOps

Responsible AI controls

Education

Bachelor’s degree or higher in a relevant field

Tools

Azure

AWS

GCP

Snowflake

BigQuery

Redshift

Relational databases

Document databases

CI/CD tooling

Observability tools

Job description

Location: Hyderabad

Experience: 6-11 Years

Role: Azure Data Engineer (Lead and Senior Data Engineer)

Mandatory Skills:

• Enterprise data architecture; solution design; data modeling; Data Warehouse; Data Lake; Lakehouse; Medallion patterns
• Python; SQL; ETL/ELT; APIs; automation; testing; code review; troubleshooting; performance tuning
• Azure, AWS or GCP; Snowflake; BigQuery; Redshift; Relational and document databases
• Data quality; metadata; lineage; cataloging; classification; MDM; privacy; security
• CI/CD; DataOps; DevSecOps; observability; migration; stakeholder management; technical mentoring
• AI/ML data foundations; RAG; vector search; MLOps; Responsible AI controls