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EXL

Lead Data Engineer, Azure

EXL

Azure Lead Data Engineer building ETL/ELT pipelines with Azure Data Factory, Snowflake, and DBT. Improving data integration, quality, governance, and reliability for cloud-native analytics.

Posted 9/10/2026full-timeBengaluru • 🇮🇳 IndiaSeniorWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and developing ETL/ELT pipelines using Azure Data Factory, Snowflake, and DBT, while ensuring data quality and governance. Proficient in SQL and experienced in collaborating with cross-functional teams to deliver technical solutions in cloud-native environments.

Highest-signal resume keywords
Azure Data FactorySQL ProficiencySnowflake ExpertiseDBT KnowledgeData Governance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
ETL DevelopmentData Integration WorkflowsSQL QueriesData TransformationData Quality StandardsData Pipeline OptimizationCloud-Based Data EnvironmentsPythonPySparkCI/CD Pipelines
Soft Skills
Problem-SolvingCommunicationCollaboration
Tools & Technologies
Azure Cloud PlatformSnowSQLDataStageNetezzaAzure Data LakeAzure SynapseAzure FunctionsPower BITableau
Industry Keywords
Data EngineeringData WarehousingData GovernanceMetadata ManagementData Catalog Tools

Tech Stack

Tools & technologies
AzureCloudETLPySparkPythonSQLTableau

About the role

Key responsibilities & impact
  • Design and develop ETL/ELT pipelines using Azure Data Factory, Snowflake, and DBT
  • Build and maintain data integration workflows from various data sources to Snowflake
  • Write efficient and optimized SQL queries for data extraction and transformation
  • Work with stakeholders to understand business requirements and translate them into technical solutions
  • Monitor, troubleshoot, and optimize data pipelines for performance and reliability
  • Maintain and enforce data quality, governance, and documentation standards
  • Collaborate with data analysts, architects, and DevOps teams in a cloud-native environment

Requirements

What you’ll need
  • Strong experience with Azure Cloud Platform services
  • Proven expertise in Azure Data Factory (ADF) for orchestrating and automating data pipelines
  • Proficiency in SQL for data analysis and transformation
  • Hands-on experience with Snowflake and SnowSQL for data warehousing
  • Practical knowledge of DBT (Data Build Tool) for transforming data in the warehouse
  • Experience working in cloud-based data environments with large-scale datasets
  • Experience with DataStage, Netezza, Azure Data Lake, Azure Synapse, or Azure Functions
  • Familiarity with Python or PySpark for custom data transformations
  • Understanding of CI/CD pipelines and DevOps for data workflows
  • Exposure to data governance, metadata management, or data catalog tools
  • Knowledge of business intelligence tools such as Power BI or Tableau is a plus
  • Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or a related field
  • 8+ years of experience in data engineering roles using Azure and Snowflake
  • Strong problem-solving, communication, and collaboration skills

Benefits

Comp & perks
  • Hybrid work arrangement