Lead Data Consultant, Manager

Line of Service

Advisory

Industry/Sector

Not Applicable

Specialism

Technology Strategy

Management Level

Manager

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 Manager - Data Engineering, you’ll work as part of a team of problem solvers, helping clients design, architect and deliver modern data platforms and analytics solutions across leading cloud platforms, while delivering high quality client service and operational efficiency. Toronto is the preferred location for this role.

Enhancing your leadership style, you motivate, develop and inspire others to deliver quality. You are responsible for coaching, leveraging team member’s unique strengths, and managing performance to deliver on client expectations. With your growing knowledge of how business works, you play an important role in identifying opportunities that contribute to the success of our Firm. You are expected to lead with integrity and authenticity, articulating our purpose and values in a meaningful way. You embrace technology and innovation to enhance your delivery and encourage others to do the same.

Responsibilities include but are not limited to:

• Lead the architecture, design and delivery of scalable, secure and resilient cloud data platforms and data engineering solutions across Azure, GCP and/or AWS.
• Translate business and technical requirements into end-to-end cloud solution architectures, including data ingestion, storage, processing, integration, security, governance, observability and consumption patterns.
• Design and oversee batch and real-time data pipelines using modern orchestration and processing technologies, including Apache Airflow, Spark and Databricks, together with cloud-native data services.
• Provide technical leadership across data platform modernization, cloud migration, data warehouse/lakehouse implementation, data integration and analytics initiatives.
• Define and promote engineering standards and reusable patterns for data quality, metadata-driven processing, error handling, monitoring, logging, lineage, testing, CI/CD and infrastructure automation.
• Evaluate technology and architecture options, articulate trade-offs, and provide pragmatic recommendations based on scalability, performance, security, maintainability and cost.
• Take ownership of projects and workstreams, ensuring successful planning, estimation, budgeting, execution, risk management and completion.
• Lead technical discussions and architecture workshops with clients and stakeholders, communicating complex concepts clearly to both technical and non-technical audiences.
• Partner with project and team leadership to ensure collective ownership of quality, timelines and deliverables, and contribute technical input to proposals, RFP responses and solution estimates.
• Coach and mentor data engineers and architects, review solution designs and technical deliverables, and use feedback and review as opportunities to deepen team expertise.
• Address delivery challenges, technical risks and conflicts proactively, engaging with clients, team members and other stakeholders and escalating where appropriate.
• Uphold and reinforce professional and technical standards, the Firm’s code of conduct and independence requirements.

Experiences and skills you’ll use to solve

• Significant hands-on experience in data engineering, cloud data platforms and the delivery of enterprise analytics solutions, with demonstrated experience leading technical teams or workstreams.
• Strong cloud solution architecture skills, with the ability to design end-to-end data solutions spanning networking and connectivity, identity and access management, security, storage, compute, integration, observability, resilience and cost optimization.
• Strong experience with at least one major cloud platform (Microsoft Azure, Google Cloud Platform (GCP) or Amazon Web Services (AWS)), together with the ability to apply architecture and data engineering principles across cloud platforms.
• Strong experience designing and building scalable batch and streaming data pipelines, including ingestion, transformation, curation and data serving patterns.
• Hands-on experience with Apache Airflow for workflow orchestration, including DAG design, scheduling, dependencies, retries, monitoring, parameterization and production operationalization.
• Strong experience with modern data processing and lakehouse technologies such as Databricks, Apache Spark and Delta Lake, or comparable cloud-native technologies.
• Experience with relevant cloud data services such as Azure Data Factory, Azure Synapse Analytics, ADLS, Event Hubs, Microsoft Fabric, Google Cloud Storage, BigQuery, Pub/Sub, Dataflow, AWS Glue, S3, Redshift, EMR and/or Kinesis.
• Strong knowledge of data architecture and modelling concepts, including dimensional modelling, data warehousing, lakehouse architectures, ETL/ELT, data integration and data lifecycle management.
• Proficiency in SQL and Python and experience developing maintainable, testable and reusable data engineering solutions.
• Experience implementing data quality, error handling, reconciliation, monitoring, alerting, lineage and operational support frameworks for production data platforms.
• Understanding of cloud security and governance concepts including least-privilege access, RBAC/IAM, secrets management, encryption, private connectivity, data classification and auditability.
• Experience with software engineering and DevOps practices including Git, code reviews, automated testing, CI/CD and infrastructure as code; experience with Terraform, Bicep or CloudFormation is an asset.
• Strong consulting and communication skills, including the ability to facilitate technical workshops, present architecture decisions and trade-offs, influence stakeholders and translate business requirements into technical solutions.
• Experience contributing to solution estimation, proposals, RFP responses, technical pre-sales and/or client presentations is an asset.
• Relevant cloud, data engineering or solution architecture certifications from Microsoft, Google Cloud, AWS and/or Databricks are considered an asset

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.

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:

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, Coaching and Feedback, Communication, Creativity, Data Anonymization, Data Architecture Development, 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 {+ 33 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 ( 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 (