About the role
Mission Your mission is to design and build scalable data platforms and services using Python and Spark, deliveringData-as-a-Service and Infrastructure-as-a-Service capabilitiesto internal and external clients. You will contribute to modern data pipelines, cloud-native deployments, and API-driven data access in an Azure ecosystem.
Day-to-Day Responsibilities
- Design, develop, and maintaindata pipelines and RESTful APIsusing Python (3.8+) and Apache Spark.
- Build and optimizedistributed data processing workflows(batch & streaming) for large-scale datasets.
- Contribute todata platform architectureleveraging Azure services (e.g., Data Lake, Databricks, AKS).
- FollowGit-based workflows(GitHub/GitLab) and enforce versioning and code quality standards.
- Work withinAgile methodologies(Scrum/Kanban) using Jira.
- Deploy applications and data pipelines usingCI/CD pipelines (Jenkins/Azure DevOps).
- Containerize and deploy services on**Kubernetes (AKS)**ensuring scalability and reliability.
- Collaborate with stakeholders toanalyze business requirementsand translate them into data solutions.
- Communicate effectively with clients and internal teams; synthesize and present findings clearly.
- Partner withOps/DevOps teamsto ensure production readiness, monitoring, and reliability.
- Ensure compliance withdata governance, security, and best engineering practices.
- Continuously improve platform performance, cost efficiency, and maintainability.
Technical Skills
Strong expertise in:
- Python (3.8+) with focus ondata engineering and backend development(3+ years)
- Apache Spark / PySpark fordistributed data processing(2+ years)
- SQL & NoSQL databases (data modeling, optimization)
- Git (GitHub/GitLab) and collaborative development workflows
- CI/CD tools (Jenkins, Azure DevOps) and automation (1+ year)
- Object-Oriented Programming and clean architecture principles
Proficient in:
- Azure ecosystem (e.g., Azure Data Lake, Databricks, AKS, Functions)
- Data pipeline orchestration (Airflow, Azure Data Factory, or equivalent)
- Containerization (Docker) and orchestration (Kubernetes / AKS)
- RESTful API development and integration
- Agile methodologies (Scrum/Kanban), TDD, and unit testing
- UNIX/Linux environments and best practices
Desired / Plus
- Experience withreal-time data streaming(Kafka, Spark Streaming, Event Hub)
- Knowledge ofdata governance, data quality, and lineage tools
- Familiarity withFlask / FastAPI / OpenAPIfor data service exposure
- Infrastructure-as-Code (Terraform, ARM templates, Bicep)
- Monitoring tools (Prometheus, Grafana, Azure Monitor)
- Strong documentation and presentation skills
Competencies
- Strongclient-focused mindsetwith a data-driven approach to problem solving
- Ability to work acrossdata, development, and operations teams
- Excellent collaboration skills in aglobal and cross-functional environment
- Strong analytical thinking with attention to detail and performance optimization
- Ability to clearly communicate complex data concepts to technical and non-technical audiences
- Proactive mindset with continuous improvement orientation
Experience Needed
- Minimum3+ years in Data Engineering / Big Data development
- Hands-on experience withPython and Spark in production environments
- Experience with**cloud platforms (preferably Azure)**and containerized deployments
- Familiarity withDevOps and ITIL processesis a plus
- Ability to quickly adapt to new technologies and environments
Educational Requirements
- Master’s Degree in Engineering, Computer Science, or related field
Certifications (Nice to Have)
- Azure Data Engineer Associate (DP-203) or equivalent
- Databricks / Spark certifications
- Agile certifications (Scrum, SAFe)
Languages
- Fully bilingual: English and French
==================================
Développeur Big Data & Data Engineering (Python / Spark / Azure)
Mission Votre mission est de concevoir et développer des plateformes de données scalables en utilisant Python et Spark, afin de fournir des capacités deData-as-a-Service et Infrastructure-as-a-Serviceaux clients internes et externes. Vous contribuerez à la mise en place de pipelines de données modernes, de déploiements cloud natifs et d’APIs d’accès aux données dans un environnement Azure.
Responsabilités quotidiennes
- Concevoir, développer et maintenir despipelines de données et APIs RESTen Python (3.8+) et Apache Spark.
- Développer et optimiser destraitements distribués(batch et streaming) pour des volumes de données importants.
- Contribuer à l’architecture de laplateforme dataen s’appuyant sur les services Azure (Data Lake, Databricks, AKS, etc.).
- Appliquer les bonnes pratiques de développement via des workflowsGit (GitHub/GitLab).
- Travailler en méthodologie**Agile (Scrum/Kanban)**avec Jira.
- Déployer les solutions via des pipelinesCI/CD (Jenkins, Azure DevOps).
- Conteneuriser et déployer les applications sur**Kubernetes (AKS)**en garantissant la scalabilité et la résilience.
- Collaborer avec les parties prenantes pouranalyser et clarifier les besoins métier.
- Communiquer efficacement avec les équipes et les clients, et synthétiser les retours.
- Travailler étroitement avec les équipesOps/DevOpspour assurer la mise en production et la supervision.
- Garantir le respect desbonnes pratiques (sécurité, gouvernance des données, architecture).
- Améliorer en continu les performances, la maintenabilité et les coûts des solutions.
Compétences techniques
Expertise solide en :
- Python (3.8+) orientédata engineering et développement backend(3+ ans)
- Apache Spark / PySpark pour letraitement distribué(2+ ans)
- SQL & NoSQL (modélisation et optimisation des données)
- Git (GitHub/GitLab) et workflows collaboratifs
- Outils CI/CD (Jenkins, Azure DevOps) (1+ an)
- Programmation orientée objet et bonnes pratiques de conception
Maîtrise de :
- Environnement Azure (Data Lake, Databricks, AKS, Functions, etc.)
- Orchestration de pipelines (Airflow, Azure Data Factory ou équivalent)
- Conteneurisation (Docker) et orchestration (Kubernetes / AKS)
- Développement et intégration d’APIs REST
- Méthodologies Agile (Scrum/Kanban), TDD, tests unitaires
- Environnements UNIX/Linux et bonnes pratiques associées
Atouts (Nice to Have)
- Expérience enstreaming temps réel(Kafka, Spark Streaming, Event Hub)
- Connaissances engouvernance des données, qualité des données et data lineage
- Maîtrise deFlask / FastAPI / OpenAPI
- Infrastructure-as-Code (Terraform, ARM, Bicep)
- Outils de monitoring (Prometheus, Grafana, Azure Monitor)
- Excellentes compétences en documentation et présentation
Compétences comportementales
- Forte orientationclient et qualité de service
- Capacité à collaborer avec des équipesdata, développement et opérations
- Excellentes aptitudes relationnelles dans un environnementinternational
- Esprit analytique avec souci du détail et de la performance
- Capacité à vulgariser des concepts techniques complexes
- Proactivité et démarche d’amélioration continue
Expérience requise
- Minimum3 ans d’expérience en Data Engineering / Big Data
- Expérience concrète avecPython et Spark en production
- Expérience sur des environnements**cloud (Azure de préférence)**et conteneurisés
- Connaissance des processusDevOps / ITILest un plus
- Capacité d’adaptation rapide à de nouveaux environnements techniques
Formation
- Diplôme d’ingénieur ou Master en informatique, data ou domaine connexe
Certifications (souhaitées)
- Microsoft Azure Data Engineer Associate (DP-203)
- Certifications Databricks / Spark
- Certifications Agile (Scrum, SAFe)
Langues
- Bilingue : français et anglais
Not the right fit? Search for Python jobs in Montréal, QC
About CGI
Insights you can act on to achieve trusted outcomes.
We are insights-driven and outcomes-focused to help accelerate returns on your investments. Across 21 industry sectors and 400 locations worldwide, we provide comprehensive, scalable and sustainable IT and business consulting services that are informed globally and delivered locally.
We value your opinions and welcome your comments and questions on our posts here on LinkedIn. Please keep a polite, professional and constructive tone. We remove comments containing objectionable language and derogatory views. We do not allow content that is unrelated to the subject, and we remove discriminatory and racist comments as well as spam and advertising.
Note that content on this page contains general information regarding CGI’s services and initiatives and should not be considered direct business advice. To engage in a discussion with one of our experts, please make a request through https://www.cgi.com/en/contact-us
Similar jobs you might like
About the role
Mission Your mission is to design and build scalable data platforms and services using Python and Spark, deliveringData-as-a-Service and Infrastructure-as-a-Service capabilitiesto internal and external clients. You will contribute to modern data pipelines, cloud-native deployments, and API-driven data access in an Azure ecosystem.
Day-to-Day Responsibilities
- Design, develop, and maintaindata pipelines and RESTful APIsusing Python (3.8+) and Apache Spark.
- Build and optimizedistributed data processing workflows(batch & streaming) for large-scale datasets.
- Contribute todata platform architectureleveraging Azure services (e.g., Data Lake, Databricks, AKS).
- FollowGit-based workflows(GitHub/GitLab) and enforce versioning and code quality standards.
- Work withinAgile methodologies(Scrum/Kanban) using Jira.
- Deploy applications and data pipelines usingCI/CD pipelines (Jenkins/Azure DevOps).
- Containerize and deploy services on**Kubernetes (AKS)**ensuring scalability and reliability.
- Collaborate with stakeholders toanalyze business requirementsand translate them into data solutions.
- Communicate effectively with clients and internal teams; synthesize and present findings clearly.
- Partner withOps/DevOps teamsto ensure production readiness, monitoring, and reliability.
- Ensure compliance withdata governance, security, and best engineering practices.
- Continuously improve platform performance, cost efficiency, and maintainability.
Technical Skills
Strong expertise in:
- Python (3.8+) with focus ondata engineering and backend development(3+ years)
- Apache Spark / PySpark fordistributed data processing(2+ years)
- SQL & NoSQL databases (data modeling, optimization)
- Git (GitHub/GitLab) and collaborative development workflows
- CI/CD tools (Jenkins, Azure DevOps) and automation (1+ year)
- Object-Oriented Programming and clean architecture principles
Proficient in:
- Azure ecosystem (e.g., Azure Data Lake, Databricks, AKS, Functions)
- Data pipeline orchestration (Airflow, Azure Data Factory, or equivalent)
- Containerization (Docker) and orchestration (Kubernetes / AKS)
- RESTful API development and integration
- Agile methodologies (Scrum/Kanban), TDD, and unit testing
- UNIX/Linux environments and best practices
Desired / Plus
- Experience withreal-time data streaming(Kafka, Spark Streaming, Event Hub)
- Knowledge ofdata governance, data quality, and lineage tools
- Familiarity withFlask / FastAPI / OpenAPIfor data service exposure
- Infrastructure-as-Code (Terraform, ARM templates, Bicep)
- Monitoring tools (Prometheus, Grafana, Azure Monitor)
- Strong documentation and presentation skills
Competencies
- Strongclient-focused mindsetwith a data-driven approach to problem solving
- Ability to work acrossdata, development, and operations teams
- Excellent collaboration skills in aglobal and cross-functional environment
- Strong analytical thinking with attention to detail and performance optimization
- Ability to clearly communicate complex data concepts to technical and non-technical audiences
- Proactive mindset with continuous improvement orientation
Experience Needed
- Minimum3+ years in Data Engineering / Big Data development
- Hands-on experience withPython and Spark in production environments
- Experience with**cloud platforms (preferably Azure)**and containerized deployments
- Familiarity withDevOps and ITIL processesis a plus
- Ability to quickly adapt to new technologies and environments
Educational Requirements
- Master’s Degree in Engineering, Computer Science, or related field
Certifications (Nice to Have)
- Azure Data Engineer Associate (DP-203) or equivalent
- Databricks / Spark certifications
- Agile certifications (Scrum, SAFe)
Languages
- Fully bilingual: English and French
==================================
Développeur Big Data & Data Engineering (Python / Spark / Azure)
Mission Votre mission est de concevoir et développer des plateformes de données scalables en utilisant Python et Spark, afin de fournir des capacités deData-as-a-Service et Infrastructure-as-a-Serviceaux clients internes et externes. Vous contribuerez à la mise en place de pipelines de données modernes, de déploiements cloud natifs et d’APIs d’accès aux données dans un environnement Azure.
Responsabilités quotidiennes
- Concevoir, développer et maintenir despipelines de données et APIs RESTen Python (3.8+) et Apache Spark.
- Développer et optimiser destraitements distribués(batch et streaming) pour des volumes de données importants.
- Contribuer à l’architecture de laplateforme dataen s’appuyant sur les services Azure (Data Lake, Databricks, AKS, etc.).
- Appliquer les bonnes pratiques de développement via des workflowsGit (GitHub/GitLab).
- Travailler en méthodologie**Agile (Scrum/Kanban)**avec Jira.
- Déployer les solutions via des pipelinesCI/CD (Jenkins, Azure DevOps).
- Conteneuriser et déployer les applications sur**Kubernetes (AKS)**en garantissant la scalabilité et la résilience.
- Collaborer avec les parties prenantes pouranalyser et clarifier les besoins métier.
- Communiquer efficacement avec les équipes et les clients, et synthétiser les retours.
- Travailler étroitement avec les équipesOps/DevOpspour assurer la mise en production et la supervision.
- Garantir le respect desbonnes pratiques (sécurité, gouvernance des données, architecture).
- Améliorer en continu les performances, la maintenabilité et les coûts des solutions.
Compétences techniques
Expertise solide en :
- Python (3.8+) orientédata engineering et développement backend(3+ ans)
- Apache Spark / PySpark pour letraitement distribué(2+ ans)
- SQL & NoSQL (modélisation et optimisation des données)
- Git (GitHub/GitLab) et workflows collaboratifs
- Outils CI/CD (Jenkins, Azure DevOps) (1+ an)
- Programmation orientée objet et bonnes pratiques de conception
Maîtrise de :
- Environnement Azure (Data Lake, Databricks, AKS, Functions, etc.)
- Orchestration de pipelines (Airflow, Azure Data Factory ou équivalent)
- Conteneurisation (Docker) et orchestration (Kubernetes / AKS)
- Développement et intégration d’APIs REST
- Méthodologies Agile (Scrum/Kanban), TDD, tests unitaires
- Environnements UNIX/Linux et bonnes pratiques associées
Atouts (Nice to Have)
- Expérience enstreaming temps réel(Kafka, Spark Streaming, Event Hub)
- Connaissances engouvernance des données, qualité des données et data lineage
- Maîtrise deFlask / FastAPI / OpenAPI
- Infrastructure-as-Code (Terraform, ARM, Bicep)
- Outils de monitoring (Prometheus, Grafana, Azure Monitor)
- Excellentes compétences en documentation et présentation
Compétences comportementales
- Forte orientationclient et qualité de service
- Capacité à collaborer avec des équipesdata, développement et opérations
- Excellentes aptitudes relationnelles dans un environnementinternational
- Esprit analytique avec souci du détail et de la performance
- Capacité à vulgariser des concepts techniques complexes
- Proactivité et démarche d’amélioration continue
Expérience requise
- Minimum3 ans d’expérience en Data Engineering / Big Data
- Expérience concrète avecPython et Spark en production
- Expérience sur des environnements**cloud (Azure de préférence)**et conteneurisés
- Connaissance des processusDevOps / ITILest un plus
- Capacité d’adaptation rapide à de nouveaux environnements techniques
Formation
- Diplôme d’ingénieur ou Master en informatique, data ou domaine connexe
Certifications (souhaitées)
- Microsoft Azure Data Engineer Associate (DP-203)
- Certifications Databricks / Spark
- Certifications Agile (Scrum, SAFe)
Langues
- Bilingue : français et anglais
Not the right fit? Search for Python jobs in Montréal, QC
About CGI
Insights you can act on to achieve trusted outcomes.
We are insights-driven and outcomes-focused to help accelerate returns on your investments. Across 21 industry sectors and 400 locations worldwide, we provide comprehensive, scalable and sustainable IT and business consulting services that are informed globally and delivered locally.
We value your opinions and welcome your comments and questions on our posts here on LinkedIn. Please keep a polite, professional and constructive tone. We remove comments containing objectionable language and derogatory views. We do not allow content that is unrelated to the subject, and we remove discriminatory and racist comments as well as spam and advertising.
Note that content on this page contains general information regarding CGI’s services and initiatives and should not be considered direct business advice. To engage in a discussion with one of our experts, please make a request through https://www.cgi.com/en/contact-us