Face To Face Discussion For GCP Data Engineer @ Chennai on 26-Sep

HCLTech

Chennai District

Hybrid

INR 1,200,000 - 1,800,000

Full time

14 days+
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Job summary

HCLTech in Chennai is seeking an experienced GCP Data Engineer to design, develop, and maintain scalable data pipelines using GCP technologies. The role focuses on BigQuery, Dataproc, Apache Airflow, PySpark, and Python to support analytics and data warehousing initiatives.

The candidate will work on batch and streaming processing, build reliable data workflows, and collaborate with data architects, analysts, and business stakeholders to meet requirements.

Qualifications

  • 4+ years of experience in data engineering.
  • Experience designing scalable data pipelines on GCP.
  • Hands-on with BigQuery, Dataproc, Airflow, PySpark, Python.
  • Strong collaboration with stakeholders and ability to translate requirements.

Responsibilities

  • Design, develop, and maintain scalable ETL/ELT data pipelines on GCP.
  • Build and optimize data solutions using BigQuery for large-scale analytics.
  • Develop batch and streaming data processing with PySpark on Dataproc.
  • Create, schedule, and monitor workflows using Apache Airflow (Cloud Composer).
  • Integrate data from databases, APIs, cloud storage, and enterprise apps.
  • Implement data quality checks, validation, and monitoring.

Skills

ETL/ELT design
Data pipelines
BigQuery
PySpark
Python
CI/CD/DevOps
Agile methodology

Tools

BigQuery
Dataproc
Apache Airflow
Cloud Composer
Python

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.
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