Line of Service

Advisory

Industry/Sector

Not Applicable

Specialism

Technology Strategy

Management Level

Senior Associate

Job Description & Summary

At PwC, our people in infrastructure focus on designing and implementing robust, secure IT systems that support business operations. They enable the smooth functioning of networks, servers, and data centres to optimise performance and minimise downtime.

In infrastructure engineering at PwC, you will focus on designing and implementing robust and scalable technology infrastructure solutions for clients. Your work will involve network architecture, server management, and cloud computing experience.

As an Azure Data Engineer, you will play a crucial role in designing, building, and maintaining our enterprise data platform on the Microsoft Azure cloud. Your primary responsibility will be developing scalable, reliable, and efficient data pipelines to ingest, transform, and serve data to business analysts, data scientists, and operational systems. This role demands a deep understanding of modern data architecture, a passion for automation, and hands-on expertise with the Azure data stack.

Meaningful work you’ll be a part of

As a Senior Associate, Azure Data Engineer, you’ll work as part of a team of problem solvers, helping to solve business issues, deliver high quality client service and operational efficiency. Responsibilities include but are not limited to:

Architect, design, and own the development of robust, end-to-end data pipelines for our production environment, utilizing Azure Data Factory, Azure Databricks, and Azure Synapse Analytics.

Lead the design and implementation of advanced data models within our Azure Data Lake. Champion the Medallion Architecture (Bronze/Silver/Gold) and build complex business logic into scalable, efficient transformations using PySpark and Delta Lake.

Develop ETL/ELT processes to ingest data from a wide variety of sources, including relational databases (SQL, Oracle), APIs, and streaming data feeds.

Implement data models, transformations, and cleansing routines to prepare data for analytics.

Automate data workflows and implement CI/CD practices for data pipelines using Azure DevOps or GitHub Actions to ensure quality and rapid deployment.

Monitor, troubleshoot, and optimize data solutions for performance, scalability, and cost-effectiveness.

Proactively identify and resolve performance bottlenecks in data pipelines. This includes hands-on Spark job tuning, query optimization, data partitioning strategies, and implementing cost-control measures across our Azure data services.

Work closely with data analysts, data scientists, and business stakeholders to understand their data requirements and deliver high-quality data solutions.

Mentor junior data engineers through code reviews, paired programming, and technical guidance. Establish and document coding standards, best practices, and reusable frameworks to elevate the entire team's technical capabilities.

Partner directly with data scientists, analysts, and business leaders to translate complex business requirements into robust, scalable, and reliable technical solutions.

Ensure data quality, integrity, and governance by implementing best practices, data validation checks, and robust documentation.

Experiences and skills you’ll use to solve

Microsoft Azure Data Engineer Associate (DP-203) certification is required, or the ability to obtain it within the first 2 months.

5-7 years of dedicated, hands-on experience in a data engineering role, with a proven track record of delivering complex projects to production.

Deep, hands-on expertise and production experience with core Azure data services: Azure Data Factory (ADF), Azure Databricks, and Azure Data Lake Storage (ADLS Gen2).

Advanced proficiency in Azure Data Factory, including creating dynamic, metadata-driven pipelines, managing complex control flows and triggers, and configuring Self-Hosted Integration Runtimes for hybrid data movement.

Expert-level proficiency in SQL and Python. You must have extensive, production-level experience with PySpark for large-scale, distributed data processing.

Proven experience ingesting data from diverse and complex sources, including real-time streaming data from Kafka or Azure Event Hubs, REST APIs, and files from SFTP servers

Proven experience designing and implementing end-to-end data solutions on Azure, demonstrating a strong grasp of modern ELT patterns, data warehousing (star schema), and data lake architectures (e.g., Medallion).

Deep understanding of data storage optimization within ADLS Gen2, including file format selection (e.g., Delta, Parquet), partitioning strategies, and data lifecycle management for cost and performance.

Demonstrated ability to troubleshoot and solve complex, ambiguous data problems in a production environment, including performance tuning and root cause analysis.

Bachelor's degree in computer science, Engineering, Information Technology, or related field.

Significant hands-on experience with Azure Synapse Analytics (Dedicated and Serverless SQL Pools).

Experience in the healthcare or life sciences domain, with a strong understanding of healthcare data standards and interoperability protocols like HL7 v2.x and FHIR. This includes experience parsing, transforming, and modeling complex clinical or claims data.

Experience integrating with specialized or legacy data sources using protocols such as HTTP and MLLP for healthcare data feeds.

Experience building and managing CI/CD pipelines for data engineering projects using Azure DevOps.

Proficiency with Infrastructure as Code (Bicep preferred, Terraform is a plus).

Strong understanding of Azure security best practices (Managed Identities, Azure Key Vault, Private Endpoints).

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 $84,700 - $134,700.  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. 

Why you’ll love PwC 

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. 

Education (if blank, degree and/or field of study not specified)

Degrees/Field of Study required:

Degrees/Field of Study preferred:

Certifications (if blank, certifications not specified)

Required Skills

Optional Skills

Accepting Feedback, Accepting Feedback, Active Listening, Amazon Web Services (AWS), Analytical Thinking, Architectural Engineering, Business Continuity, Cloud Architectures, Cloud Compliance, Cloud Infrastructure, Cloud Migration, Cloud Virtualization, Communication, Continuous Deployment, Continuous Integration/Continuous Delivery (CI/CD), Creativity, Data Infrastructure, DevOps Practices, Disaster Recovery, Embracing Change, Emotional Regulation, Empathy, Google Cloud Platform (GCP), Hardware Troubleshooting, Hybrid Cloud {+ 31 more}

Desired Languages (If blank, desired languages not specified)

Travel Requirements

Not Specified

Available for Work Visa Sponsorship?

No

Government Clearance Required?

No

Job Posting End Date

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).

Nous tenons à répondre à vos besoins tout au long du processus de demande d’emploi, d’entrevue et d’embauche. Si vous avez besoin de mesures d’adaptation pour être parfaitement à l’aise, faites-le-nous savoir à l’étape de la demande d’emploi.

L’utilisation de l’intelligence artificielle (IA) dans le domaine du recrutement en est à ses balbutiements. Nous savons que vous pourriez vous demander comment et pourquoi nous y avons recours. À certains stades de notre processus de recrutement, nous comptons sur l’IA pour améliorer votre expérience. Par exemple, pendant l’examen du curriculum vitæ ou l’élaboration d’une liste de recommandations personnalisées, un agent conversationnel pourrait vous demander des précisions ou fixer avec vous un rendez-vous pour l’entrevue. L’IA nous aide à mieux lutter contre les préjugés, car l’évaluation des candidats se fait de façon juste et équitable, sans que les informations d’identification comme le nom ou le sexe soient connues. Elle nous permet également de mieux repérer les bons candidats pour un poste et d’évaluer le lien entre leurs compétences, leur expérience et leurs chances de réussir chez PwC Canada. Bien que l’IA facilite certaines étapes de notre processus de recrutement, les décisions finales d’embauche sont toujours prises par des personnes. Pour en savoir plus sur l’utilisation et la protection de vos données personnelles, consultez notre politique sur la protection des renseignements confidentiels (https://www.pwc.com/ca/fr/privacy-policy.html).