Senior Associate, Data Engineer

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.

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.

• 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, Big Query, 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 Dev Ops practices: version control (Git), CI/CD (Git Hub Actions, Azure Dev Ops, Code Pipeline), and Infrastructure as Code (Terraform/Cloud Formation/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.

• 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…