Azure Senior Data Lead
India
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Job Description
Azure Senior Data Lead
Bangalore, Karnataka

Job Summary

We are seeking a highly skilled Azure Data Engineer to design, develop, and optimize enterprise-scale data platforms on Microsoft Azure. The ideal candidate will have strong expertise in building modern data lakes and lakehouse architectures, implementing batch and streaming data pipelines, data modeling, performance tuning, and cost optimization. The role involves working with large-scale datasets using Azure-native services and Databricks technologies to deliver reliable, scalable, and high-performance data solutions.

Key Responsibilities

  • Design, develop, and maintain scalable data ingestion and transformation pipelines using Azure Data Factory (ADF) and Azure Databricks.
  • Build and manage enterprise data platforms using ADLS Gen2, Medallion Architecture (Bronze, Silver, Gold layers), and Lakehouse principles.
  • Develop robust ETL/ELT solutions using PySpark, Spark SQL, and Python.
  • Implement and optimize batch and streaming data processing solutions.
  • Design and maintain Delta Live Tables (DLT) for dependable and automated data transformation workflows.
  • Build streaming pipelines using Auto Loader, Structured Streaming, and Delta Lake technologies.
  • Establish and govern data assets through Unity Catalog for centralized security, governance, and metadata management.
  • Create and maintain dimensional and enterprise data models to support analytics and reporting requirements.
  • Develop and optimize Power BI datasets and semantic models for business intelligence and reporting.
  • Implement CI/CD pipelines for data engineering solutions using Azure DevOps or similar tools.
  • Monitor and improve data platform performance through workload optimization, partitioning strategies, caching, and query tuning.
  • Drive cloud cost optimization initiatives across Azure Data Lake, Databricks, storage, and compute resources.
  • Ensure adherence to data governance, security, compliance, and best practices.
  • Collaborate with architects, business stakeholders, analysts, and application teams to understand requirements and deliver data solutions.

Skill Requirements

Azure Data Services

  • Azure Data Factory (ADF)
  • Azure Data Lake Storage Gen2 (ADLS)
  • Azure Databricks
  • Delta Lake
  • Unity Catalog

Data Engineering & Processing

  • Medallion Architecture
  • Batch Processing
  • Streaming Data Processing
  • Delta Live Tables (DLT)
  • Auto Loader
  • ETL/ELT Frameworks

Programming & Analytics

  • PySpark
  • Spark SQL
  • Python
  • Data Modelling
  • SQL

Reporting & Visualization

  • Power BI
  • Data Visualization
  • Semantic Models

DevOps & Automation

  • CI/CD Pipelines
  • Azure DevOps
  • Git
  • Infrastructure Automation

Performance & Optimization

  • Query Optimization
  • Spark Performance Tuning
  • Partitioning Strategies
  • Workload Management
  • Cost Optimization

Other Requirements

  • Experience with large-scale Azure Data Platform implementations.
  • Strong understanding of Lakehouse Architecture and Delta Lake.
  • Experience working in Agile/Scrum environments.
  • Knowledge of data governance and security frameworks.

Microsoft Azure Data Engineering certifications are highly desirable.
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Information at a Glance

Why HCLTech?

At HCLTech, you'll supercharge your potential. You'll find your career. And you'll find your spark. All at a place that knows that helping its customers stay on top starts by putting its people first.

HCLTech is a global technology company, home to more than 223,000 people across 60 countries, delivering industry-leading capabilities centered around digital, engineering, cloud and AI, powered by a broad portfolio of technology services and products. We work with clients across all major verticals, providing industry solutions for Financial Services, Manufacturing, Life Sciences and Healthcare, Technology and Services, Telecom and Media, Retail and CPG, and Public Services. Consolidated revenues as of 12 months ending June 2026 totaled $14.8 billion.