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 ResponsibilitiesData Engineering & Architecture

- Design, build, and maintain scalable and high-performance data pipelines on GCP.
- Develop and manage up-to-date 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 & SkillsEducation & 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 RequirementsCore 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 RequirementsSkill 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 |

📌 GCP Senior Data Engineer (India)
🏢 HCL Technologies
📍 India