• Create end-to-end integration tests for data pipelines and improve pipelines accordingly

• Translate requirements into clear design specifications, and present solutions for team review, incorporating feedback and direction from team lead and team members in a collaborative development environment.

• Conduct Knowledge Transfer and training sessions, ensuring staff receive the required knowledge to support and improve upon the system. Develop learning activities using review-watch-do methodology & demonstrate the ability to prepare and present.

• Develop documentation and materials as part of a review and knowledge transfer to other team members



Qualifications
Must Have:

- Demonstrated fluency in Python, with knowledge of its best practices, coding conventions, and application in building robust, scalable data pipelines.

- Experience with Data pipeline and workflow development, orchestration, deployment, and automation and specializing in programming and pipelines to create and managing the dataflow and movement of data.

- Experience with Cloud data platforms, data management and data exchange tools and technologies.

- Experience with Commercial and open-source data and database development and management and specializing in data storage setting and managing cloud Data As a Service (DaaS), application Database as a Service (DBaaS), Data Warehouses as a Service (DWaaS), and other storage platforms (both in the cloud and on-premise).

- Understanding and working knowledge of iterative product development cycles (Discovery, Agile, Beta, Live)

- Experience contributing to version-controlled, shared codebases using git (Azure DevOps, GitHub, Bitbucket) and participating in pull request code reviews.

- Experience in Continuous Integration/Continuous Development/Deployment (CI/CD) and Data provisioning Automation.

- Proficiency in SQL and python, with hands-on experience using Databricks and Spark SQL for data modeling and transformation tasks.

General Skills
• Experience with Cloud data platforms, data management and data exchange tools and technologies
• Experience with Commercial and opensource data and database development and management and specializing in data storage setting and managing cloud Data As a Service (DaaS). application Database as a Service (DBaaS), Data Warehouses as a Service (DWaaS), and other storage platforms (both in the cloud and on-premise).
• Experience with Data pipeline and workflow development, orchestration, deployment, and automation and specializing in programming and pipelines to create and managing the dataflow and movement of data.
• Experience with Cloud data engineer must be familiar and experienced with different programming languages and be able to integrate with many different platforms to create data pipelines, automate tasks, and write scripts.
• Experience in DataOPS principle, best practice, and implementation and Agile project development and deployment
• Experience in Continuous Integration/Continuous Development/Deployment (CI/CD) and Data provisioning Automation
• Experience with digital product, data analysis, data exchange, data provisioning, and data security
• Extensive expert experience in designing/developing and implementing data conversation and migration of VLD (Very large Data) of Online analytical processing (OLAP) and online transaction processing (OLTP) environments to Cloud Software-as-a-service (SaaS), Platform-as-a-service (PaaS) and Infrastructure-as-a-service (IaaS) environments.
• Experience in design, development and implementation of fact/dimension model, data mapping, data warehouse, data lake and data lakehouse for enterprise
• Experience managing Cloud Data services for project delivery, including storage, repositories, Data Lake, Data Lakehouse, key vault, virtual machine, disk, etc.
• Experience with structured, semi-structured, unstructured data collection, ingestion, provisioning and exchange technological development of enterprise data warehouse and data lake and data lakehouse solutions and operational support.
• Experience with DataOPS performance monitoring and tuning
• Excellent analytical, problem-solving and decision-making skills; verbal and written communication skills; presentation skills; interpersonal and negotiation skills
• A team player with a track record for meeting deadlines



Summary
If you are interested in the Senior DataOps/Cloud Data Engineer role in Toronto, please apply online at www.randstad.ca. Qualified candidates will be contacted.


Randstad Canada is committed to fostering a workforce reflective of all peoples of Canada. As a result, we are committed to developing and implementing strategies to increase the equity, diversity and inclusion within the workplace by examining our internal policies, practices, and systems throughout the entire lifecycle of our workforce, including its recruitment, retention and advancement for all employees. In addition to our deep commitment to respecting human rights, we are dedicated to positive actions to affect change to ensure everyone has full participation in the workforce free from any barriers, systemic or otherwise, especially equity-seeking groups who are usually underrepresented in Canada's workforce, including those who identify as women or non-binary/gender non-conforming; Indigenous or Aboriginal Peoples; persons with disabilities (visible or invisible) and; members of visible minorities, racialized groups and the LGBTQ2+ community.

Randstad Canada is committed to creating and maintaining an inclusive and accessible workplace for all its candidates and employees by supporting their accessibility and accommodation needs throughout the employment lifecycle. We ask that all job applications please identify any accommodation requirements by sending an email to accessibility@randstad.ca to ensure their ability to fully participate in the interview process.