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At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision‑making and driving business growth. Those in machine learning ops engineering at PwC will focus on developing and implementing operational processes and infrastructure to support machine learning models and algorithms. Your work will involve enabling the smooth deployment and maintenance of machine learning systems within an organisation.

As an Azure Data Engineer, Manager, you will lead teams to deliver end‑to‑end data engineering projects on Azure. You will combine technical expertise with leadership skills to design, build, and deploy robust data solutions. You will collaborate with Project Leads and Practice Leads, support RFPs and pre‑sales activities, and ensure high‑quality delivery aligned with client objectives.

• Lead teams to deliver end‑to‑end Azure data engineering projects, ensuring technical excellence and timely delivery.
• Act as an expert in Azure Data Platform, including Azure Data Factory (ADF), Azure Databricks, Synapse Analytics, Event Hub, Blob Storage, Fabric.
• Design and build scalable data pipelines, including data ingestion, curation, normalisation, and transformation.
• Implement data quality checks, error handling, and monitoring frameworks to ensure reliability.
• Apply strong knowledge of data modelling and data warehouse concepts to design optimised solutions.
• Troubleshoot issues during development and testing phases, ensuring smooth deployment of data pipelines.
• Integrate and optimise Power BI solutions for reporting and analytics, ensuring seamless connectivity with Azure data sources.
• Collaborate with stakeholders to define architecture and technical approach; support pre‑sales and RFP responses with solution design input.
• Promote DevOps/DataOps practices, CI/CD pipelines, and Infrastructure as Code.
• Mentor team members and contribute to knowledge sharing and best practices within the practice.

• Bachelor’s degree in Computer Science, Engineering, or related field; Master’s degree or MBA preferred.
• Proven experience in leading onshore/offshore teams to deliver complex Azure data engineering projects.
• Deep expertise in Azure Data Platform services: Data Factory, Databricks, Synapse Analytics, Event Hub, Blob Storage.
• Strong proficiency in SQL, Python, and data architecture principles.
• Solid understanding of data modelling, data warehousing, and ETL/ELT processes.
• Hands‑on experience with Power BI.
• Experience with data quality frameworks, error handling, and pipeline optimisation.
• Knowledge of cloud security, IAM, compliance, and cost optimisation strategies.
• Excellent communication, stakeholder management, and leadership skills.
• Preferred certifications: Microsoft Certified: Azure Data Engineer Associate (DP‑203); Microsoft Certified: Fabric Analytics Engineer Associate; Databricks Certified Data Engineer Professional.
• This role does not require professional engineering licensure and is not classified as a formal engineering position under provincial regulatory definitions. While individuals with a P.Eng designation are welcome to apply, the responsibilities of this role do not involve the practice of professional engineering as defined by applicable legislation.
• PwC Canada is committed to cultivating an inclusive, hybrid work environment. Exact expectations for your team can be discussed with your interviewer.

This newly created role reflects our commitment to growth and delivering distinctive value for our clients and stakeholders.

The salary range for this position is $112,400 - $162,400. The posted salary range represents the expected hiring range for PwC locations in major city centres. Given our national recruiting approach, ranges may vary for positions in other locations. At PwC Canada, base salary is determined by your skills, experience, qualifications and work location. In addition to base salary, eligible employees may have opportunities to participate in variable incentive pay programs which are designed to reward individual and firm‑wide achievements. We are committed to offering competitive compensation and adhere to all relevant pay transparency legislation. During the hiring process, our Talent Acquisition team will provide details about our comprehensive total rewards package.

We’re inspiring and empowering our people to change the world. Powered by the latest technology, you’ll be a part of diverse teams helping public and private clients build trust and deliver sustained outcomes. This meaningful work, and our continuous development environment, will take your career to the next level. We reward your impact, and support your wellbeing, through a competitive compensation package, inclusive benefits and flexibility programs that will help you thrive in work and life. Learn more about our Application Process and Total Rewards Package at: https://jobs-ca.pwc.com/ca/en/life-at-pwc.

PwC Canada acknowledges that we work and live across Turtle Island, on the land that is now known as Canada, which are the lands of the ancestral, treaty and unceded territories of the First Nations, Métis and Inuit Peoples. We recognize the systemic racism, colonialism and oppression that Indigenous Peoples have experienced and still go through, and we commit to allyship and solidarity.

We’re committed to providing accommodation throughout the application, interview, and employment process. If you require accommodation to be at your best, please let us know during the application process.

The use of artificial intelligence (AI) in recruiting is just getting started, so we know you have questions about how and why we use it. At certain points during our recruiting process, we rely on AI to improve your experience. This could be during resume review or curating personalized job recommendations, asking you clarifying questions via a chatbot or during our interview scheduling to improve your experience. Our use of AI helps ensure we combat bias by evaluating candidates equally and fairly, without seeing identity information, such as your name, or gender for example). AI also helps us better predict successful hires by reviewing all applicants for a role and the relationship between your skills, experience and likely success at PwC Canada. While AI supports parts of our recruitment process, final hiring decisions always involve human review. For more information about our use and protection of your data, please refer to our Privacy Policy https://www.pwc.com/ca/en/privacy-policy.html.