Data Engineer

• 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.

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., * 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

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