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Position Description Location: Toronto/Montreal Preferred Languages: Bilingual (English/French) Preferred Employment Type: Full-Time CGI is seeking an experienced Senior Data Platform Engineering Specialist to join our growing Data Platform Engineering consulting practice within the Emerging Technologies team. As a full-time member of CGI, you will become part of a collaborative team of architects, engineers, and consultants delivering enterprise technology solutions for some of Canada's leading public and private sector organizations. While you may be assigned to one or more client engagements, you will remain a permanent member of CGI's Data Platform Engineering practice, collaborating with teammates, contributing to reusable data assets, and continuously developing your technical and consulting expertise. In this role, you will help clients modernize how they ingest, store, process, govern, and analyze data. You will design, implement, and support modern data platforms (Data Lakes, Data Warehouses, and Lakehouses) that improve data democratization, operationalize machine learning models, and drive business intelligence. Success in this role requires curiosity, adaptability, strong data engineering fundamentals, and a passion for continuous learning. Rather than specializing strictly in a single technology stack, you will leverage sound DataOps principles to deliver innovative, scalable, and secure data infrastructure across a variety of industries, technologies, and client environments. Your future duties and responsibilities Data Platform Engineering Design, build, and support scalable data platforms that enable batch and real-time data processing, analytics, and AI workloads. Implement and manage modern data architectures, including Lakehouses (e.g., Databricks), Cloud Data Warehouses (e.g., Snowflake), and robust ETL/ELT pipelines. Develop reusable data platform capabilities that enable self-service data ingestion, transformation, and exploration for downstream analysts and data scientists. Optimize data storage, compute scaling, and query performance across large-scale distributed data systems. DataOps & Automation Design and implement modern data delivery pipelines using CI/CD, Data as Code, and automation. Automate the provisioning of data infrastructure, workspace configuration, and data pipeline orchestration (e.g., using Apache Airflow or dbt). Improve data quality, pipeline reliability, operational stability, and engineering efficiency through automated testing and continuous improvement. Data Governance & Security Implement robust data governance frameworks, fine-grained access controls, and data lineage tracking (e.g., Unity Catalog). Integrate data security best practices throughout the data lifecycle, ensuring compliance, data masking, and secure data sharing. Support incident response for data pipelines, data quality root cause analysis, and capacity planning. Cloud & Infrastructure Engineering Design, deploy, and support secure data solutions across public cloud environments (AWS, Azure, GCP). Implement foundational data infrastructure using Infrastructure as Code (IaC) such as Terraform. Apply cloud networking, identity, resiliency, and cloud cost optimization (FinOps) best practices for data workloads. Innovation & Emerging Technologies Evaluate emerging data technologies, table formats (e.g., Apache Iceberg, Delta Lake), and engineering practices that improve client outcomes. Contribute proof-of-concepts, reusable data accelerators, engineering assets, and innovation initiatives. Support enterprise adoption of Artificial Intelligence, MLOps, and Retrieval-Augmented Generation (RAG) capabilities by building the foundational data layers required to support them. Consulting & Collaboration Partner directly with client stakeholders to understand business challenges and translate requirements into practical technical solutions. Collaborate with CGI architects, engineers, and consultants to deliver successful client outcomes. Participate in architecture reviews, technical workshops, design sessions, and strategic planning activities. Support proposals, technical estimates, proof-of-concepts, and solution development when required. Mentor junior data engineers and contribute to knowledge sharing across CGI's Data Platform Engineering practice. Required Qualifications To Be Successful In This Role Engineering Experience Demonstrated experience designing, implementing, and supporting enterprise data platforms, data lakes, or data warehouses within complex business environments. Experience delivering Data Engineering, DataOps, Big Data, or Analytics solutions. Experience contributing to data modernization, cloud migration, or enterprise BI/AI initiatives. Strong understanding of modern data architecture practices and the ability to apply them across diverse client environments. Ability to quickly learn and apply new data technologies and engineering approaches. Data Platform Engineering Experience with concepts such as: Data Lakes, Data Warehouses, and Lakehouse architectures ETL / ELT pipeline design and orchestration DataOps & CI/CD for Data Data Governance, Cataloging, and Lineage Distributed Data Processing Open Table Formats (Delta Lake, Iceberg) Core Data Technologies Deep expertise in one or more enterprise data platforms and tools, including: Databricks / Apache Spark Snowflake Apache Airflow, dbt (data build tool) Event Streaming (Apache Kafka, Confluent, Azure Event Hubs) Cloud Engineering (Adjacent Skills) Experience working with enterprise cloud platforms and deploying infrastructure via code, including: Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP) Infrastructure as Code (Terraform, Bicep, ARM) Containers & Kubernetes (understanding how to run data workloads in containers) Programming & Automation Strong proficiency in languages used for data processing and automation: Python SQL (Advanced tuning and analytics) Scala or Java (Bonus) Bash / PowerShell Professional Skills Strong analytical and problem-solving skills. Excellent written and verbal communication skills. Ability to communicate effectively with both technical and business stakeholders. Strong collaboration and relationship-building skills. Adaptability and a willingness to learn new technologies. Passion for engineering excellence and continuous improvement. Experience Mentoring Or Supporting Other Engineers. Experience That Will Help You Succeed The following experience is considered an asset but is not required: Artificial Intelligence & MLOps Experience building infrastructure to support AI Platforms, Generative AI, or MLOps. Understanding vector databases and data prep for Retrieval-Augmented Generation (RAG). General Platform Engineering Experience with developer self-service, Internal Developer Platforms (IDPs), or traditional CI/CD pipelines (GitHub Actions, GitLab CI/CD). Cloud Financial Management Experience with FinOps, specifically optimizing compute costs for massive data platforms like Snowflake or Databricks. Industry Experience Experience supporting clients within Financial Services, Government, Healthcare, Telecommunications, Insurance, Utilities, or other regulated industries. Types of Client Engagements As a member of CGI's Data Platform Engineering practice, you may contribute to initiatives such as: Data Modernization & Cloud Migration Enterprise Lakehouse Implementation DataOps Transformation & Automation Artificial Intelligence / MLOps Enablement Real-time Analytics & Streaming Data Platforms Enterprise Data Governance Initiatives Technologies We Commonly Work With Depending on the client engagement, you may work with technologies such as: Data & Analytics Platforms Databricks (Delta Lake, Unity Catalog) Snowflake Microsoft Fabric AWS Glue / Athena / Redshift Google BigQuery Orchestration & Transformation Apache Airflow dbt (data build tool) Apache Kafka Cloud Platforms & Infrastructure AWS, Microsoft Azure, Google Cloud Platform Terraform, Ansible Kubernetes, Docker Programming & Query Languages Python, SQL, Scala What Success Looks Like Successful Senior Data Platform Engineers at CGI: Deliver secure, scalable, and reliable data architectures that create measurable client value and enable analytics/AI. Build trusted relationships with clients through technical expertise and professionalism. Adapt quickly to new data ecosystems, industries, and client environments. Contribute reusable data engineering assets, automation, and best practices to the Data Platform practice. Mentor teammates and actively share knowledge across the organization. Continuously improve data operations processes and delivery practices. Demonstrate ownership, accountability, collaboration, and commitment to continuous learning. Why Join CGI? Joining CGI means becoming part of a long-term consulting practice focused on helping organizations solve complex technology challenges. As a member of our Data Platform Engineering practice, you will collaborate with experienced architects, data scientists, and consultants while supporting enterprise clients across a wide range of industries. As client needs evolve, you will have opportunities to work on new engagements, broaden your technical expertise, and continue building your career while remaining part of a collaborative engineering community. At CGI, you will have opportunities to: Deliver enterprise-scale cloud, DataOps, AI, and data modernization initiatives. Work across multiple industries and diverse technology environments. Collaborate with experienced architects and technical leaders. Contribute to innovation, reusable data assets, and emerging technology initiatives. Continuously develop your technical and consulting skills. Grow your career into Data Architect, Principal Data Architect, Technical Practice Lead, or Director, Data Platform Engineering Specialist. CGI is providing a reasonable estimate of the pay range for this role. The determination of this range includes factors such as skill set level, geographic market, experience and training, and licenses and certifications. Compensation decisions depend on the facts and circumstances of each case. A reasonable estimate of the current range is $95,000-$145,000. This role is a future opening. Together, as owners, let’s turn meaningful insights into action. Life at CGI is rooted in ownership, teamwork, respect and belonging. Here, you’ll reach your full potential because… You are invited to be an owner from day 1 as we work together to bring our Dream to life. That’s why we call ourselves CGI Partners rather than employees. We benefit from our collective success and actively shape our company’s strategy and direction. Your work creates value. You’ll develop innovative solutions and build relationships with teammates and clients while accessing global capabilities to scale your ideas, embrace new opportunities, and benefit from expansive industry and technology expertise. You’ll shape your career by joining a company built to grow and last. You’ll be supported by leaders who care about your health and well-being and provide you with opportunities to deepen your skills and broaden your horizons. At CGI, we value the strength that diversity brings and are committed to fostering a workplace where everyone belongs. We collaborate with our clients to build more inclusive communities and empower all CGI partners to thrive. As an equal-opportunity employer, being able to perform your best during the recruitment process is important to us. If you require an accommodation, please inform your recruiter. That same commitment to fairness extends to how we use technology. To support our recruitment team, AI tools may be used to help assess applications though they never replace human judgement. All hiring decisions remain entirely in the hands of our recruitment professionals. To learn more about accessibility at CGI, contact us via email. Please note that this email is strictly for accessibility requests and cannot be used for application status inquiries. Come join our team—one of the largest IT and business consulting services firms in the world.

Ce que vous ferez

Design, implement, and support scalable modern data platforms including Lakehouses and Data Warehouses to enable AI and analytics workloads. Collaborate with clients to modernize data ingestion, processing, and governance while automating infrastructure through DataOps principles.

Exigences

Requires demonstrated experience in enterprise data platform engineering, cloud infrastructure (AWS/Azure/GCP), and proficiency in Python and SQL. Candidates should have expertise in distributed data processing and modern orchestration tools like Airflow or dbt.

Compétences indiquées

• Python · Souhaitée
• SQL · Souhaitée
• Terraform · Souhaitée
• Amazon Web Services · Souhaitée
• Microsoft Azure · Souhaitée
• Google Cloud · Souhaitée
• CI/CD · Souhaitée

Autres compétences pertinentes

Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.

• Databricks
• Snowflake
• Apache Spark
• Apache Airflow
• dbt
• Python
• SQL
• Terraform
• AWS
• Azure
• GCP
• Kafka
• CI/CD
• DataOps
• Data Governance
• ETL/ELT

Domaines d’emploi

• Data & Analytics
• Consulting
• Technology
• Engineering
• Software