Senior Data Platform Engineering Specialist

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. #LI-AB19
• Use of the term ‘engineering’ in this job posting refers to the technical sense related to Information Technology (IT) and does not imply that the individual practices engineering or possesses the requisite license as prescribed by the applicable provincial or territorial engineering regulator. We are seeking individuals with expertise in IT engineering-related functions, but licensure from an engineering regulator is not a prerequisite for this position. Engineering is a regulated profession in Canada which is restricted in terms of use of titles and designation.

Skills:

• Finance&Ops Apps Solution Arch

What you can expect from us: