Job descriptionTitle: Data Engineer (Google Cloud Platform - GCP)
Location: Hybrid – 3 Days per Week On-Site
Duration: 6 Months
Pay Range: C$53 INC
Role Summary
We are seeking a skilled Data Engineer with hands-on Google Cloud Platform (GCP) experience to design, build, and maintain scalable data pipelines and cloud-based data solutions. The ideal candidate will have expertise in data warehousing, ETL/ELT development, big data technologies, and GCP services to support enterprise analytics and business intelligence initiatives.
Key Responsibilities
Design, develop, and maintain scalable batch and real-time data pipelines on GCP.
Build and optimize data ingestion frameworks from multiple structured and unstructured data sources.
Develop ETL/ELT processes using GCP-native services and modern data engineering tools.
Design and implement data models for analytics, reporting, and machine learning use cases.
Manage and optimize data storage solutions using BigQuery and Cloud Storage.
Monitor data quality, performance, security, and governance standards.
Collaborate with business stakeholders, data analysts, architects, and data scientists to deliver enterprise data solutions.
Implement CI/CD, automation, and DevOps practices for data engineering workloads.
Troubleshoot data processing issues and optimize pipeline performance.
Ensure compliance with data security and privacy requirements.
Required Skills:
Strong experience in Data Engineering and data pipeline development.
Hands-on experience with Google Cloud Platform (GCP) services including:
- BigQuery
- Cloud Storage
- Dataflow
- Pub/Sub
- Dataproc
- Cloud Composer (Airflow)
- Cloud Functions
- Cloud Run
Strong programming skills in:
- Python
- SQL
- PySpark
Experience with ETL/ELT frameworks and data integration tools.
Strong knowledge of data warehousing concepts and dimensional modeling.
Experience working with relational and NoSQL databases.
Knowledge of real-time and streaming data architectures.
Understanding of CI/CD pipelines, GitHub, and DevOps practices.
Experience with data quality, metadata management, and governance.
Preferred Skills
- Experience with Apache Spark, Hadoop, Kafka, and Airflow.
- Exposure to machine learning data pipelines and MLOps.
- Experience with Terraform or Infrastructure as Code (IaC).
- Knowledge of containerization technologies such as Docker and Kubernetes.
- Experience in Banking, Financial Services, Insurance, or large enterprise environments.
Required Qualifications
- Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, or a related field.
- Excellent analytical and problem-solving skills.
- Strong communication and stakeholder management skills.
- Experience working in Agile/Scrum environments.