GCP Senior Data Engineer
Confirmed on the employer's own hiring board on Oct 7, 2026. First seen by Alion on Oct 6, 2026.
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