Senior Technical Lead
India
Apply now
Job Description
Senior Technical Lead
Bengaluru, Karnataka

Job Summary

Job Title: Data Engineer – DBT & BigQuery

Role Summary

We are looking for an experienced Data Engineer with strong expertise in DBT (Data Build Tool), Google BigQuery, SQL, and cloud data engineering. The role will focus on building scalable data transformation pipelines, developing analytical data models, implementing data-quality controls, and optimizing BigQuery performance and cost.

Key Responsibilities

  • Design, develop, and maintain data transformation pipelines using DBT.
  • Develop scalable data models and analytical datasets in Google BigQuery.
  • Write and optimize complex SQL queries for large-volume datasets.
  • Build DBT models using staging, intermediate, and mart layers.
  • Implement incremental models, snapshots, seeds, macros, tests, hooks, and reusable DBT packages.
  • Develop dimensional models using Star/Snowflake schemas, fact tables, and dimensions.
  • Implement automated data-quality and validation tests using DBT.
  • Optimize BigQuery workloads through partitioning, clustering, query optimization, and efficient data-model design.
  • Build and maintain CI/CD pipelines for DBT deployments using Git-based development practices.
  • Troubleshoot data-pipeline failures and resolve data-quality and performance issues.
  • Maintain technical documentation, data lineage, model descriptions, and business definitions.
  • Collaborate with data analysts, BI teams, data scientists, and business stakeholders to translate requirements into scalable data solutions.
  • Follow enterprise data governance, security, access-control, and engineering standards.

 

Key Responsibilities

Job Title: Data Engineer – DBT & BigQuery

Role Summary

We are looking for an experienced Data Engineer with strong expertise in DBT (Data Build Tool), Google BigQuery, SQL, and cloud data engineering. The role will focus on building scalable data transformation pipelines, developing analytical data models, implementing data-quality controls, and optimizing BigQuery performance and cost.

Key Responsibilities

  • Design, develop, and maintain data transformation pipelines using DBT.
  • Develop scalable data models and analytical datasets in Google BigQuery.
  • Write and optimize complex SQL queries for large-volume datasets.
  • Build DBT models using staging, intermediate, and mart layers.
  • Implement incremental models, snapshots, seeds, macros, tests, hooks, and reusable DBT packages.
  • Develop dimensional models using Star/Snowflake schemas, fact tables, and dimensions.
  • Implement automated data-quality and validation tests using DBT.
  • Optimize BigQuery workloads through partitioning, clustering, query optimization, and efficient data-model design.
  • Build and maintain CI/CD pipelines for DBT deployments using Git-based development practices.
  • Troubleshoot data-pipeline failures and resolve data-quality and performance issues.
  • Maintain technical documentation, data lineage, model descriptions, and business definitions.
  • Collaborate with data analysts, BI teams, data scientists, and business stakeholders to translate requirements into scalable data solutions.
  • Follow enterprise data governance, security, access-control, and engineering standards.

 

Skill Requirements

Job Title: Data Engineer – DBT & BigQuery

Role Summary

We are looking for an experienced Data Engineer with strong expertise in DBT (Data Build Tool), Google BigQuery, SQL, and cloud data engineering. The role will focus on building scalable data transformation pipelines, developing analytical data models, implementing data-quality controls, and optimizing BigQuery performance and cost.

Key Responsibilities

  • Design, develop, and maintain data transformation pipelines using DBT.
  • Develop scalable data models and analytical datasets in Google BigQuery.
  • Write and optimize complex SQL queries for large-volume datasets.
  • Build DBT models using staging, intermediate, and mart layers.
  • Implement incremental models, snapshots, seeds, macros, tests, hooks, and reusable DBT packages.
  • Develop dimensional models using Star/Snowflake schemas, fact tables, and dimensions.
  • Implement automated data-quality and validation tests using DBT.
  • Optimize BigQuery workloads through partitioning, clustering, query optimization, and efficient data-model design.
  • Build and maintain CI/CD pipelines for DBT deployments using Git-based development practices.
  • Troubleshoot data-pipeline failures and resolve data-quality and performance issues.
  • Maintain technical documentation, data lineage, model descriptions, and business definitions.
  • Collaborate with data analysts, BI teams, data scientists, and business stakeholders to translate requirements into scalable data solutions.
  • Follow enterprise data governance, security, access-control, and engineering standards.

 

Other Requirements

Job Title: Data Engineer – DBT & BigQuery

Role Summary

We are looking for an experienced Data Engineer with strong expertise in DBT (Data Build Tool), Google BigQuery, SQL, and cloud data engineering. The role will focus on building scalable data transformation pipelines, developing analytical data models, implementing data-quality controls, and optimizing BigQuery performance and cost.

Key Responsibilities

  • Design, develop, and maintain data transformation pipelines using DBT.
  • Develop scalable data models and analytical datasets in Google BigQuery.
  • Write and optimize complex SQL queries for large-volume datasets.
  • Build DBT models using staging, intermediate, and mart layers.
  • Implement incremental models, snapshots, seeds, macros, tests, hooks, and reusable DBT packages.
  • Develop dimensional models using Star/Snowflake schemas, fact tables, and dimensions.
  • Implement automated data-quality and validation tests using DBT.
  • Optimize BigQuery workloads through partitioning, clustering, query optimization, and efficient data-model design.
  • Build and maintain CI/CD pipelines for DBT deployments using Git-based development practices.
  • Troubleshoot data-pipeline failures and resolve data-quality and performance issues.
  • Maintain technical documentation, data lineage, model descriptions, and business definitions.
  • Collaborate with data analysts, BI teams, data scientists, and business stakeholders to translate requirements into scalable data solutions.
  • Follow enterprise data governance, security, access-control, and engineering standards.

 
Apply now
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 230,000 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 September 2026 totaled $14.8 billion.