Lead Azure Data Engineer

Tata Consultancy Services; Hyderabad, Bengaluru, Mumbai; On-site; INR 3,500,000 - 5,500,000; Full time

Job summary

Tata Consultancy Services is seeking a Lead Azure Data Engineer to architect and deliver enterprise-scale data solutions on Microsoft Azure. You will guide data-lake and data-warehouse architectures, govern data pipelines, and lead cross-functional teams across multiple projects.

The role requires deep expertise in Azure data services, strong leadership, and hands-on Python/SQL skills to drive modernization, governance, and security across scalable analytics platforms.

Qualifications

• 15–20 years of experience in data engineering or cloud data platforms.
• Strong hands-on expertise with Azure data services and modern analytics.
• Experience leading architecture, governance, and data security efforts.

Responsibilities

• Lead architecture and implementation of enterprise-scale Azure data platforms.
• Design data lakes and data warehouses and govern data pipelines.
• Define best practices for security, performance, and scalability.
• Lead and mentor multiple data-engineering teams across projects.
• Drive cloud migration and data modernization initiatives.
• Establish CI/CD and DevOps practices for data platforms.
• Ensure data quality, governance, and compliance across platforms.
• Collaborate with stakeholders to define data strategies and roadmaps.

Skills

Azure Data Factory

Azure Databricks

PySpark

Azure Synapse Analytics

ADLS Gen2

Azure SQL

Python

SQL

T-SQL

Spark SQL

Data Lake

Data Warehouse

Azure DevOps

CI/CD Pipelines

RBAC

Cloud Security

Data Modeling

Governance

Metadata Management

Tools

Azure DevOps

Git

CI/CD

Job description

Dear Professionals

Greetings from Tata consultancy Services,

Job Title : Lead Azure Data Engineer

Experiernce: 15 to 20 Years

Location: Bengaluru / Hyderabad / Chennai / Pune/Mumbai

Mode of Work : Work from Office

Mode of Interview: Virtual

Role : Lead Azure Data Engineer

Experience: 15-20 Years
Location: Bengaluru / Hyderabad / Chennai / Pune

Job Summary

We are looking for an experienced Lead Azure Data Engineer to drive the design, architecture, and delivery of enterprise-scale data platforms on Microsoft Azure. The ideal candidate will possess deep expertise in modern data engineering, cloud architecture, data governance, and large-scale analytics solutions. This role requires strong technical leadership, stakeholder management, solution design, and team mentoring capabilities. Relevant Azure data engineering technologies include Azure Data Factory, Azure Databricks, Azure Synapse Analytics, ADLS Gen2, Azure DevOps, and advanced data warehousing solutions.

Key Responsibilities

• Lead the architecture and implementation of enterprise-scale Azure data platforms.
• Design and govern data lakes, data warehouses, and real-time data processing frameworks.
• Define best practices for data engineering, security, performance tuning, and scalability.
• Lead development teams in building robust ETL/ELT pipelines using Azure services.
• Drive cloud migration and data modernization initiatives.
• Establish CI/CD and DevOps practices for data platforms.
• Ensure data quality, governance, compliance, and security standards.
• Collaborate with business stakeholders, architects, and leadership teams to define data strategies.
• Conduct technical reviews, solution assessments, and performance optimization activities.
• Mentor and manage teams of data engineers across multiple projects. [EP-JD_Azur...gineer ING | Word], [JD - Sr Az...a Engineer | Word]

Required Skills

• Expertise in Azure Data Factory (ADF).
• Strong hands-on experience with Azure Databricks and PySpark.
• Deep knowledge of Azure Synapse Analytics, ADLS Gen2, and Azure SQL.
• Strong proficiency in Python, SQL, T-SQL, Spark SQL.
• Experience designing large-scale Data Lake and Data Warehouse solutions.
• Expertise in Azure Key Vault, Managed Identity, RBAC, and cloud security.
• Experience with Azure DevOps, Git, CI/CD Pipelines, and Infrastructure as Code.
• Strong understanding of data modeling, governance, metadata management, and data quality