GCP Data Lead

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.

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

 

Skill Evaluation Matrix

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

Other Requirements

Education & Experience

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

1.Google Cloud Professional Data Engineer certification is preferred.