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Position Purpose
The GCP Data Engineer will be part of the Data & Analytics team, responsible for designing, building, and maintaining scalable data pipelines and cloud-based data platforms on Google Cloud Platform (GCP).
This role focuses on transforming raw data into reliable and efficient data systems that enable advanced analytics, reporting, and data-driven decision-making.
The Data Engineer will collaborate with Data Scientists, Architects, Project Managers, and Business stakeholders on implementation, migration, modernization, and optimization initiatives.
Key Responsibilities
• Design, build, and maintain scalable data pipelines on GCP
• Develop and optimize batch and real-time data processing solutions
• Build and manage data lakes and data warehouses
• Develop and maintain datasets for analytics and reporting
• Improve data quality, reliability, and efficiency
• Create solution design and technical documentation
• Work independently and as part of cross-functional teams
• Assist in pre-sales activities by providing effort estimates and technical inputs
• Collaborate with Project Management to ensure on-time, on-budget delivery
• Implement DevOps and CI/CD practices for data pipelines
Competencies
Personal
• Strong analytical and problem-solving skills
• High energy, ownership mindset, and accountability
• Flexible and results-oriented
• Strong communication and stakeholder management skills
Leadership
• Ability to guide junior team members
• Work effectively with diverse technical and business teams
• Provide technical mentoring and best practices
Operations
• Manage multiple projects and priorities effectively
• Deliver customer-focused solutions
• Optimize performance and resource utilization
Technical
• Strong understanding of cloud-native data architecture
• Ability to communicate complex technical concepts clearly
• Experience with Agile/Scrum methodologies
Technical Skills
GCP Core Services
• BigQuery
• Cloud Storage
• Cloud Dataflow
• Cloud Dataproc
• Pub/Sub
• Cloud Composer (Airflow)
• Cloud Functions
• Cloud Run
Programming & Data
• Python (Pandas, NumPy, PySpark)
• SQL (advanced querying and optimization)
• Spark (Batch & Streaming)
Data Engineering & Integration
• ETL/ELT pipeline development
• Data modeling (Star & Snowflake schema)
• Real-time streaming architectures
• API integrations and REST services
DevOps & Containerization
• CI/CD (GitHub Actions, Jenkins, or similar)
• Docker
• Kubernetes
• Infrastructure as Code (Terraform preferred)
Education, Experience and Certification
• Bachelor’s degree in Computer Science, Engineering, MIS, or related field
• 5–8 years of experience in Data Engineering
• 3+ years of hands-on experience with Google Cloud Platform
• 2+ years of experience building containerized applications
• Strong experience in designing and deploying data pipelines in cloud environments
• Google Cloud Professional Data Engineer certification (Preferred)
