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 contemporary 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, Ap

📌 Lead Data Consultant, Manager (Toronto)
🏢 PwC
📍 Toronto