Azure Data Migration Engineer (1882)
- Toronto, ON
- Hybride
- Publié 31 août 2026
- 1 poste
90 $–100 $ / heure
Ouvre un site externe
- Type d’emploi
- Contrat
- Niveau d’expérience
- Expérimenté · 5+ ans
- Formation minimale
- Baccalauréat
- Postuler avant le
- 30 sept. 2026
- Langue de l’offre
- anglais
- Heures de travail
- 40 heures par semaine
- Présence au bureau
- 3 jours par semaine
- Niveau d’expérience
- Mid-Senior level
- Mode de candidature
- La candidature directe est offerte
Résumé du poste
Support the migration of Capital Market Investment Analytics assets to Snowflake and Azure Cloud platforms. Develop a migration framework to accelerate the transition of data pipelines and ETL processes while maintaining existing software infrastructure.
Détails du poste
Azure Data Migration Engineer (1882) NOTE: HYBRID work model, 3-days on-site in Toronto/week Type: 12-month contract Rate: $90-100/hr SKILLS: 5+ years Azure Cloud Migration, Data Migration, PL/SQL, SQL, Snowflake, T-SQL, Python, AKS Industry: Capital Markets DESCRIPTION: Responsible for supporting the migration of the Capital Market Investment Analytics team’s assets to Snowflake and Azure Cloud enterprise platforms. You will work alongside the software developers and investment professionals on the team in support of their migration to the Cloud. You will report to the Senior Manager, Solution & Quality Engineering. Develop a Data and Cloud migration framework that accelerates the migration of the team’s assets to the organization’s Snowflake Data and Azure Cloud platforms Assist with the migration of the team’s assets to the organization’s Cloud platforms Emphasis will be placed on migrating Data Pipelines and ETL processes Maintain and improve the team's software solutions and infrastructure which runs all aspects of the team's systematic investment process including trading, execution and research. Contribute to the team’s continuous improvement process and help to develop software and data engineering best practices and standards, particularly with respect to deployment and management of assets to Data and Cloud platforms Develop new solutions and enhance existing solutions in support of the Capital Markets investment desks that the team supports. Responsible for completion of an acceptable volume of work and for the communication of status of personal work plans and tasks required to design, develop, and test assigned projects. Actively participate in the team’s agile ceremonies and work planning processes. Responsible for maintaining currency in technological trends and directions, continually upgrading personal technical and IT skills through research, education and self-motivated technology experimentation. Participate in new technology investigation and make recommendations for new technology adoption where appropriate. Other duties as assigned. REQUIREMENTS: Undergraduate or graduate degree in a quantitative discipline such as Engineering or Computer Science. Sound knowledge of information systems theories, concepts, methods, and techniques. 5+ years software design/development experience with at least 3 years full-time working as a data engineer, preferably within the financial industry. Communicate and interact effectively with systems professionals and Capital Markets business users with minimal background in information technology. Excellent organizational, analytical and problem-solving skills. Experience building data analytics and data engineering solutions, ex. Data pipelines and ETL processes. Expertise migrating Data and Data Engineering assets to cloud platforms (ex., migrating data/databases and stored procedures to Snowflake) is a must. Expertise in migrating analytic scripts (ex. , migrating Python analytic scripts to Azure AKS) is a nice-to-have. Experience with the following technologies: Database and Data engineering: Snowflake, Airflow/Astronomer, SQL Server, Oracle, Stored Procedures. Experience with DBT and SSIS is a nice-to-have Containers: Kubernetes, Docker Cloud Technologies: Azure, AKS DevOps/Agile: Git, Jenkins, Jira, Nexus. Reporting: Experience with PowerBI is a nice-to-have Web Development: experience with common web development frameworks Streamlit, React, Flask, FastAPI, Django is a nice to have Expertise in the following languages: SQL, Python Experience with common financial data providers is an asset (ex., Bloomberg, Refinitiv, S&P Xpressfeed). Experience using AI models and code assistants (ChatGPT, Claude Sonnet, Copilot, etc.) in particular for Cloud and Data migration tasks is nice to have. Experience working in an agile environment and with modern development methodologies such as Test-Driven Development, Continuous Delivery and Scrum Experience migrating web applications to cloud platforms (ex., migrating React/Django web applications to Azure/AKS) is a nice-to-have Experience in the financial industry required. Completion of the Canadian Securities Course and/or CFA candidacy is an asset. NOTE: As part of our hiring process, we use AI‑based systems to support initial applicant screening. TO APPLY: https://directitrecruiting.com/job/azure-data-migration-eng-1882/
Ce que vous ferez
Support the migration of Capital Market Investment Analytics assets to Snowflake and Azure Cloud platforms. Develop a migration framework to accelerate the transition of data pipelines and ETL processes while maintaining existing software infrastructure.
Exigences
Requires a degree in a quantitative discipline and 5+ years of software design experience, including 3 years as a data engineer in the financial industry. Expertise in migrating databases and stored procedures to Snowflake is mandatory.
Compétences indiquées
- Kubernetes · Souhaitée
- SQL · Souhaitée
- Docker · Souhaitée
- Jira · Souhaitée
- Git · Souhaitée
- Python · Souhaitée
Autres compétences pertinentes
Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.
- Azure Cloud Migration
- Data Migration
- PL/SQL
- SQL
- Snowflake
- T-SQL
- Python
- AKS
- ETL Processes
- Kubernetes
- Docker
- Airflow
- Git
- Jenkins
- Jira
- PowerBI
Domaines d’emploi
- Data & Analytics
- Technology
- Software
- Finance & Accounting
- Engineering
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