Face To Face Discussion For GCP Data Engineer @ Chennai on 19-Sep

HCLTech; Chennai District; Hybrid; INR 1,200,000 - 1,800,000; Full time

Job summary

HCLTech in Chennai is seeking an experienced GCP Data Engineer to design, build, and maintain scalable data pipelines on Google Cloud Platform. You will leverage BigQuery, Dataproc, Apache Airflow, PySpark and Python to support analytics, reporting, and data warehousing initiatives.

The role emphasizes CI/CD, DevOps practices, and collaboration with Data Analysts and Business stakeholders to deliver reliable data solutions and performance optimization in a fast-paced environment.

Qualifications

• 4+ years of experience in data engineering or a related field.
• Strong hands-on experience with Google Cloud Platform and data pipeline design.
• Experience with CI/CD, DevOps practices and Agile methodologies.

Responsibilities

• Design, develop, and maintain scalable ETL/ELT data pipelines on GCP.
• Build and optimize data solutions using BigQuery for large-scale analytics and reporting.
• Develop batch and streaming data processing applications using PySpark on Dataproc.
• Create, schedule, and monitor workflows using Apache Airflow (Cloud Composer).
• Integrate data from multiple sources including databases, APIs, cloud storage, and enterprise applications.
• Implement data quality checks, validation frameworks, and monitoring solutions.
• Optimize query performance, partitioning, clustering, and cost management in BigQuery.
• Collaborate with Data Architects, Data Analysts, and Business stakeholders to understand requirements.
• Troubleshoot production issues and ensure data pipeline reliability and performance.

Tools

BigQuery

Dataproc

Apache Airflow (Cloud Composer)

PySpark

Job description

Experience: 4+ Years
Location: Chennai
Employment Type: Full-Time

Job Summary

We are seeking an experienced GCP Data Engineer with strong expertise in designing, developing, and maintaining scalable data pipelines on Google Cloud Platform (GCP). The ideal candidate should have hands‑on experience with BigQuery, Dataproc, Apache Airflow, PySpark, and Python for building enterprise‑grade data solutions supporting analytics, reporting, and data warehousing initiatives.

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT data pipelines on GCP.
• Build and optimize data solutions using BigQuery for large-scale analytics and reporting.
• Develop batch and streaming data processing applications using PySpark on Dataproc.
• Create, schedule, and monitor workflows using Apache Airflow (Cloud Composer).
• Integrate data from multiple sources including databases, APIs, cloud storage, and enterprise applications.
• Implement data quality checks, validation frameworks, and monitoring solutions.
• Optimize query performance, partitioning, clustering, and cost management in BigQuery.
• Collaborate with Data Architects, Data Analysts, and Business stakeholders to understand requirements.
• Troubleshoot production issues and ensure data pipeline reliability and performance.
• Follow CI/CD, DevOps, and Agile best practices in data engineering projects.