Apptad
Actively Hiring
We help leading brands build Data and Analytics competencies
- B2B
- Growth StageExpanding market presence
Cloud Data Engineer (local to Quebec)
- |6 years of exp
- |Contract
Posted: 5 days ago• Recruiter recently active
Job Location
Remote Work Policy
In office - WFH flexibility
Visa Sponsorship
Not Available
RelocationAllowed
Skills
Data Integration
Amazon S3
Github
REST APIs
ETL
Google Bigquery
Monitoring
Elt
Alerts
Recovery
Apache Airflow
AWS Athena
CI/CD Pipelines
Error Handling
DevOps Practices
Release Automation
AWS Glue Data Catalog
Batch Ingestion
API-Based Data Ingestion
Near-Real-Time Ingestion
Change Data Capture (CDC) Ingestion
Pipeline Dependencies Management
About the job
Job Title: Cloud Data Engineer (local to Quebec)
Job Location: Montreal, QC (3 days/week onsite)
Job Duration: Long Term
Our Challenge
We are seeking a Cloud Data Engineer to design, develop, and maintain scalable data solutions on AWS and Google Cloud Platform. The successful candidate will build reliable data ingestion and processing pipelines, automate workflows, and support efficient deployment through modern DevOps practices.
Responsibilities:
- Develop cloud data solutions using AWS Athena, Amazon S3, AWS Glue Data Catalog, and Google BigQuery.
- Design and implement API-based data ingestion and integration processes.
- Consume REST APIs, extract data, and transform it for analytical use.
- Develop batch, near-real-time, and change data capture (CDC) ingestion patterns.
- Build and maintain ETL/ELT data pipelines.
- Use Apache Airflow for workflow scheduling and pipeline orchestration.
- Manage pipeline dependencies, monitoring, alerts, error handling, and recovery.
- Use GitHub for source control and collaborative development.
- Develop and maintain CI/CD pipelines and release automation.
- Support deployment processes and promote consistent DevOps practices across data engineering initiatives.
Skills:
- 6+ years experience Developing cloud data solutions using AWS Athena, Amazon S3, AWS Glue Data Catalog, and Google BigQuery.
- Design and implement API-based data ingestion and integration processes.
- Consume REST APIs, extract data, and transform it for analytical use.
- Develop batch, near-real-time, and change data capture (CDC) ingestion patterns.
- Build and maintain ETL/ELT data pipelines.
- Use Apache Airflow for workflow scheduling and pipeline orchestration.
- Manage pipeline dependencies, monitoring, alerts, error handling, and recovery.
- Use GitHub for source control and collaborative development.
- Develop and maintain CI/CD pipelines and release automation.
- Support deployment processes and promote consistent DevOps practices across data engineering initiatives.
