Data Engineer

HCLTech

City Of London

Hybrid

GBP 90,000 - 120,000

Full time

14 days+
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Job summary

HCLTech is seeking an experienced GCP Data Proficient Engineer in London to design and maintain data solutions on Google Cloud Platform. With a focus on reliability and performance, you will build scalable pipelines and optimize analytical datasets in BigQuery. Ideal candidates will have extensive experience in data engineering, strong skills in SQL and Python, and knowledge of CI/CD processes. The role offers a hybrid work model with 3 days onsite and 2 days remote.

Qualifications

  • 20+ years of experience in data engineering.
  • Strong hands-on experience with Google Cloud Platform.
  • Experience in designing, building, and operating scalable data solutions.

Responsibilities

  • Design, develop, and maintain scalable data pipelines using GCP-native services.
  • Implement batch and streaming data processing solutions using Apache Beam/Dataflow.
  • Build and optimize analytical datasets in BigQuery.

Skills

Google Cloud Platform
BigQuery
Dataflow (Apache Beam)
Pub/Sub
SQL
Python
CI/CD
Git

Tools

Terraform

Job description

Job Details

HCL is a $11 billion leading global technology enterprise consisting of over 200,000 professionals operating from 52 countries. Founded in 1976, HCL is one of India's original IT garage start-ups. For more on HCL, please visit www.hcl.com

Job Title: GCP Data Proficient Engineer

Experience: 20+ Years

Work Location: City of London, UK

Employment Type: 6 Months Contract and Permanent

Hybrid- 3 days onsite and 2 days remote

Role Summary

We are seeking a GCP Data Proficient Engineer with strong hands-on experience in designing, building, and operating scalable data solutions on Google Cloud Platform (GCP). The role requires expertise across data ingestion, processing, storage, and analytics, with a strong focus on reliability, security, and performance. The engineer will work closely with product owners, architects, and cross-functional engineering teams to deliver high-quality, data-driven solutions.

Key Responsibilities
  • Design, develop, and maintain scalable data pipelines using GCP-native services.
  • Implement batch and streaming data processing solutions using Apache Beam / Dataflow.
  • Build and optimize analytical datasets in BigQuery for reporting and advanced analytics.
  • Develop data ingestion frameworks using Pub/Sub, Cloud Storage, and Dataproc.
  • Design end-to-end data architectures aligned with GCP best practices.
  • Ensure high availability, fault tolerance, and cost optimization of data platforms.
  • Implement secure data access, encryption, and governance controls.
  • Collaborate with cloud architects to continuously improve platform maturity.
  • Write clean, efficient, and testable code using Python, SQL, or Java.
  • Implement CI/CD pipelines for data workloads using Cloud Build / Git-based pipelines.
  • Monitor data pipelines using Cloud Monitoring and Logging.
  • Troubleshoot production issues and drive root cause analysis.
Stakeholder Collaboration
  • Work closely with business teams, analysts, and downstream consumers to understand data needs.
  • Translate business requirements into technical data solutions.
  • Provide technical guidance and mentoring to junior engineers.
Required Skills & Experience
Core GCP Skills
  • Strong hands-on experience with Google Cloud Platform
  • BigQuery
  • Dataflow (Apache Beam)
  • Pub/Sub
  • Experience with IAM, service accounts, and GCP security best practices
Data & Programming
  • Strong proficiency in SQL (performance tuning and optimization)
  • Good coding experience in Python (preferred) or Java
  • Experience handling large-scale, structured and semi-structured datasets
DevOps & Quality
  • Experience with CI/CD, version control (Git), and automated testing
  • Familiarity with infrastructure-as-code (Terraform preferred)
  • Understanding of data quality, reconciliation, and validation frameworks
Good to Have
  • Exposure to data governance, lineage, and metadata management tools
  • Knowledge of machine learning data preparation pipelines on GCP
  • GCP certifications such as:
  • Google Professional Data Engineer
Behavioral & Soft Skills
  • Strong analytical and problem-solving mindset
  • Excellent communication and stakeholder management skills
  • Ownership-driven, proactive, and quality-focused
  • Ability to work in Agile / DevOps environments
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