Line of Service

Advisory

Industry/Sector

Not Applicable

Specialism

Technology Strategy

Management Level

Senior Associate

Job Description & Summary

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.

In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and implementing data pipelines, data integration, and data transformation solutions.

Meaningful work you’ll be part of 

As a Senior Associate Data Engineer at PwC, you’ll help clients design, build, and modernize data platforms that power analytics, AI, and business insights. You’ll work across cloud technologies (Azure, AWS, GCP), data warehousing, and modern data stacks to deliver scalable data pipelines, trustworthy datasets, and reliable platforms, while contributing to solution architecture, delivery excellence, and client communication. Responsibilities include but are not limited to: 

Design and build scalable batch and streaming data pipelines using Python/SQL and frameworks like Spark and Databricks.  

Develop ELT/ETL workflows and orchestration with tools such as Airflow, dbt, Azure Data Factory, AWS Glue, or GCP Cloud Composer.  

Implement data models (dimensional/Kimball, Data Vault, or lakehouse patterns) and optimize query performance.  

Stand up and manage cloud data platforms and warehouses (e.g., Snowflake, BigQuery, Redshift, Synapse) and data lakes on object storage.  

Integrate diverse data sources (APIs, files, events, databases) and ensure data quality, lineage, and governance (e.g., Great Expectations, Monte Carlo, Collibra, Purview).  

Contribute to solution architecture, documenting technical designs and assumptions; participate in estimations and delivery planning.  

Apply DevOps practices: version control (Git), CI/CD (GitHub Actions, Azure DevOps, CodePipeline), and Infrastructure as Code (Terraform/CloudFormation/Bicep).  

Implement security and compliance controls (encryption, RBAC, secrets management) aligned to client and regulatory standards.  

Support agile delivery: backlog refinement, sprint planning, demos, and retros; write unit/integration tests and maintain documentation.  

Collaborate with analysts, data scientists, and business stakeholders to translate requirements into technical solutions and reliable datasets.  

Mentor junior team members and contribute to reusable assets, accelerators, and best practices within the Data & Analytics practice.  

Experiences and skills you’ll use to solve 

Bachelor’s degree in Computer Science, Engineering, Mathematics, Information Systems, or equivalent experience.  

3–6 years of hands-on experience in data engineering, building production-grade data pipelines and data platforms.  

Strong proficiency in SQL and one or more programming languages (Python preferred; Scala/Java an asset).  

Experience with at least one major cloud platform (Azure, AWS, or GCP) for data engineering workloads.  

Practical knowledge of data warehousing and lakehouse architectures, including performance tuning and cost optimization.  

Familiarity with orchestration and transformation tooling (e.g., Airflow, dbt, ADF/Glue/Composer).  

Solid understanding of data modeling, metadata management, data quality, and governance concepts.  

Experience with Git-based workflows, CI/CD, and automated testing in data projects.  

Excellent communication and client-facing skills; ability to work in cross-functional teams and deliver in an agile environment.  

Experience with Databricks, Snowflake, Kafka/Event Hubs/Kinesis, or streaming frameworks (Structured Streaming/Flink).  

Hands-on with containers and orchestration (Docker/Kubernetes) for data workloads.  

Exposure to MLOps/feature stores and integrating data engineering with ML pipelines.  

Certifications such as Azure Data Engineer Associate, AWS Data Analytics Specialty, or Google Professional Data Engineer.  

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. 

Travel may be required based on client needs (typically up to 20–40%); hybrid work options available depending on project and office policies.  

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, Agile Scalability, Amazon Web Services (AWS), Analytical Thinking, Apache Airflow, Apache Hadoop, Azure Data Factory, Communication, Creativity, Data Anonymization, Data Architecture, Database Administration, Database Management System (DBMS), Database Optimization, Database Security Best Practices, Databricks Unified Data Analytics Platform, Data Engineering, Data Engineering Platforms, Data Infrastructure, Data Integration, Data Lake, Data Modeling, Data Pipeline {+ 28 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).