HCHCLTechVerified listing

GCP Senior Data Engineer

ChennaiOn-siteSenior

Recently posted - highest visibilityPosted 1d ago

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  • On-site in Chennai.

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  • Senior level, usually 5-8 years.

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The job post

540 words · from HCLTech's careers site

Job Summary

We are looking for a Senior Data Engineer with deep expertise in Google Cloud Platform (GCP) to design, build, and optimize scalable data ecosystems. This role is critical in enabling data-driven decision-making by developing high-performance data pipelines, ensuring data reliability, and supporting enterprise-wide analytics initiatives.

You will work closely with cross-functional stakeholders including data scientists, analysts, and business teams to translate business requirements into robust data solutions.

 

Key Responsibilities

Data Engineering & Architecture

  • Design, build, and maintain scalable and high-performance data pipelines on GCP.
  • Develop and manage modern data architectures to support batch and real-time processing needs.
  • Implement reusable frameworks to standardize data ingestion and transformation processes.

GCP-Based Data Integration

  • Leverage GCP services such as:
    • Dataflow
    • Big Query
    • Pub/Sub
    • Cloud Storage
    • Cloud SQL / Fire store
  • Build and optimize data integration workflows ensuring efficiency and scalability.

 

Data Management & Optimization

  • Optimize storage and query performance across GCP data platforms.
  • Ensure cost optimization, performance tuning, and scalable data design.

Quality, Governance & Security

  • Implement robust data quality checks, validation frameworks, and monitoring mechanisms.
  • Ensure adherence to data governance, security, and compliance standards.

Collaboration & Stakeholder Management

  • Partner with data scientists, analysts, and business stakeholders to understand requirements and deliver actionable insights.
  • Translate business problems into technical data solutions.

Operations & Reliability

  • Monitor, troubleshoot, and ensure high availability and performance of data pipelines.
  • Implement logging, alerting, and observability frameworks.

Leadership & Mentoring

  • Provide technical leadership and mentorship to junior engineers.
  • Drive best practices in coding, architecture, and deployment.

Continuous Improvement

  • Stay updated with the latest GCP innovations and data engineering best practices.
  • Proactively recommend improvements to enhance system performance and scalability.

Required Qualifications & Skills

Education & Experience

  • Bachelor’s or master’s degree in computer science, IT, or related field
  • 5-6 + years of experience in data engineering, with strong exposure to GCP

Skill Requirements

Core Technical Skills (Must Have)

  • Strong hands-on experience with:
    • Dataflow, Big Query, Pub/Sub
    • Cloud Storage, Cloud SQL, Fire store
  • Expertise in:
    • ETL/ELT processes
    • Data warehousing & data modeling
  • Strong programming skills:
    • Python, SQL

Key Competencies

  • Strong analytical and problem-solving skills
  • Attention to detail and commitment to data accuracy
  • Ability to work independently and in cross-functional teams
  • Excellent communication and stakeholder management skills

Preferred (Good-to-Have) Skills

  • GCP Certifications (Professional Data Engineer / Cloud Architect)
  • Experience with Big Data technologies (Hadoop, Spark)
  • Exposure to Machine Learning / AI workflows

Familiarity with DevOps practices & CI/CD pipelines

Other Requirements

Skill Evaluation Matrix

Skill Area

    

Mandatory

    

Expected Proficiency (0–5)

 


Data Pipeline Architecture

    

Yes

    

5

 


GCP Services (Dataflow, Big Query, Pub/Sub etc.)

    

Yes

    

5

 


Data Integration

    

Yes

    

4

 


Data Storage Optimization

    

Yes

    

4

 


Data Quality & Security

    

Yes

    

4

 


Programming (Python, SQL)

    

Yes

    

4

 


Stakeholder Collaboration

    

Yes

    

3

 


Monitoring & Troubleshooting

    

Yes

    

3

 


Leadership & Mentoring

    

Yes

    

3

 


ETL & Data Warehousing

    

No

    

3

 


Big Data (Hadoop/Spark)

    

No

    

3

 


DevOps

    

No

    

2

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