This role is hybrid and requires you to be at our client office at a minimum 5 days per month - subject to change at any time.
Your future duties and responsibilities:Roles & Responsibilities:
. Translate business requirements into scalable data engineering solutions across the Azure data platform
. Design and implement data ingestion, transformation, storage and consumption layers using ADLS, Databricks and ADF
. Develop and maintain engineering artefacts, including:
– Pipeline and workflow designs
– Data flow diagrams (landing → raw → curated → consumption)
– Job orchestration and dependency mapping
– Interface specifications for APIs/events/files
. Build high-performance Databricks pipelines (PySpark/Spark SQL) following Delta Lake best practices
. Work with data modelers to ensure pipelines align with logical/physical data models and follow naming/partitioning conventions
. Implement robust error handling, logging, monitoring and alerting frameworks for production pipelines
. Ensure all engineering deliverables meet non-functional requirements: SLAs, throughput, resilience, observability and compliance
. Collaborate with cloud/platform teams for compute clusters, networking, access, and security configurations
. Conduct code reviews, enforce engineering standards, and ensure adherence to DevOps/CI-CD practices (Azure DevOps preferred)
. Support SIT/UAT cycles — clarify build logility
Expected Skills:
.7-10 years of experience as Sr Data Engineer .
. Strong hands-on experience building and optimizing data pipelines on Azure (batch & near–real-time)
. Deep technical background with the Azure data engineering stack, including:
– Azure Data Lake (ADLS Gen2): zones, folder structures, ACLs/RBAC, security, access patterns
– Azure Databricks / Spark: notebooks, PySpark, Delta Lake, jobs, workflows, performance tuning
– Azure Data Factory / Synapse Pipelines: ingestion, orchestration, triggers, scheduling
. Solid understanding of ETL/ELT architectures, ingestion patterns (batch, streaming, events), APIs, messaging and file-based ingestion
. Experience implementing end-to-end data flows from source → landing → curated → consumption layers
. Advanced SQL and PySpark/Spark skills for developing, reviewing and optimizing pipelines
. Strong grasp of non-functional requirements: scalability, performance, reliability, observability, cost optimization, security
. Familiarity with Azure security: Key Vault, IAM/RBAC, MSI, VNET integration, encryption, masking/tokenization
. Proven experience with data platform modernization/migration projects (on-prem DBs/ETL → Azure Lakehouse)
. Ability to lead and guide offshore/onshore developers, work independently and drive engineering decisions
. Strong communication and collaboration skills — able to work with data modelers, architects, QA, cloud engineering and business stakeholders
. Training/Certifications (nice to have): DP-203 Azure Data Engineer, Azure Fundamentals, Databricks certifications, plus strong project experience
**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 an existing vacancy.**
Disclaimer : 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.
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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: Adobe SparkAzure Data FactoryAzure Data LakeBig DataBig Data & Analytics OperationDevOpsETLFinancial ServicesNoSQLReal-Time ApplianceSQLite What you can expect from us: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.
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