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Job Title: Data Engineer Vacancies: This posting is for (2) current vacancies Location: Toronto, ON | Vancouver, BC | Ottawa, ON | Calgary, AB | Halifax, NS | St John's, NL | Kelowna, BC| Prince George, BC | Montreal, QC | Québec, QC (Detailed office location information can be found by visiting this link: https://cancer.ca/en/contact-us) Work Model: Hybrid Work Model Salary Band: 5 ($83,000 - $93,000 CAD) HELP SHAPE THE FUTURE OF CANCER CARE IN CANADA The Canadian Cancer Society works tirelessly to save lives, improve lives and drive collective action against cancer. Together with patients, volunteers, donors and communities across the country, we raise funds to invest in transformative cancer research, we provide a caring support system for everyone affected by cancer and we advocate to governments to create a healthier future for all. It takes a society to take on cancer – and the Canadian Cancer Society is leading the way Join an exceptional team of Digital Strategy & Technology professionals helping to power the Canadian Cancer Society’s (CCS) operations and fuel our mission through innovative digital solutions. The Digital Strategy & Technology team is at the forefront of CCS’s digital transformation. Together, they are harnessing digital tools, data, and technology to boost fundraising capabilities and enhance the experience of everyone who interacts with us online. With a passion for continuous improvement and a commitment to making an impact, the team ensures CCS’s digital presence is strategic and engaging, helping us inspire and empower more Canadians who care about cancer every day. MAKING AN IMPACT Reporting to the Senior Manager, Data Engineering & Services, the Data Engineer is involved in designing, developing, maintaining and optimizing data platform services, meta-data driven data pipelines and data solutions using the organization’s data platforms and technologies. Deliver scalable, automated, and maintainable data pipelines, integrations, and services using modern cloud technologies and platforms. Partner with business and technical teams to design and implement data solutions that adhere to security best practices and align with data governance standards. Support a data-driven, innovation-focused engineering environment by applying modern design patterns and leveraging emerging technologies to improve how data is integrated, governed, and utilized across the organization. What You’ll Be Doing Data Engineering & Platform Development Data Pipelines Design, implement, and optimize data ingestion and transformation processes using Microsoft Fabric (Data Pipelines, Dataflows, and Notebooks) Develop end-to-end ETL/ELT workflows for structured and unstructured data Automate and orchestrate data workflows for efficiency and reliability Data Lakehouse Implement Data Lakehouse architecture leveraging modern data standards Design and optimize data models using medallion architecture Optimize storage and processing solutions for performance and cost-effectiveness Data Transformation Develop data transformations using Apache Spark in Fabric Notebooks for cleansing, aggregation, and enrichment Optimize Spark workloads, queries, and configurations for performance tuning Support legacy data platforms and integration processes as required Data Analytics Build reusable, high-quality datasets and data assets for reporting and insights 2 . Integrations & Data Pipelines Data Workflows Develop and maintain data integrations with Azure data services, external systems, and reporting platforms Implement data ingestion processes across batch and real-time workflows Develop transformation framework to support data movement and processing across systems Automate data workflows and integration processes to improve efficiency and reliability Collaboration And Documentation Coordinate with business and technical teams to translate integration requirements into scalable data solutions Support data consistency and relationships across systems through integration and data processing workflows Develop and maintain integration documentation, including data mappings and data models DevOps & Support Build And Release Management Develop and maintain CI/CD pipelines using Azure DevOps for data platform solutions Support source control, branching strategies, and automated deployment processes Contribute to infrastructure as code, orchestration, and deployment of data pipelines and services Operations And Reliability Implement monitoring, logging, and alerting for data pipelines and integrations Support performance optimization and operational reliability of data solutions Support data lifecycle processes including archiving, backup, and replication across key platforms Participate in Agile development processes, including sprint planning and iterative delivery Data Governance & Quality Governance And Security Apply data governance, compliance, and data quality standards when developing and delivering data pipelines and integrations Support lineage and metadata management using tools such as Microsoft Purview Implement and support data security controls aligned with organizational compliance standards Data Quality Perform data quality validation and monitoring across data pipelines and datasets Support adherence to established data policies, standards, and best practices Other Contribute to our culture of diversity, inclusion, belonging and equity (DIBE) by ensuring that all staff feel represented, valued, and heard across all aspects of their identity, including gender, age, religion, ethnicity, nationality, race, and sexuality. Other duties as assigned Qualifications Education / Experience: Bachelor’s or Master’s degree in computer science, information Systems, Data Engineering or related disciplines Relevant certifications preferred (e.g., Microsoft Certified Frabric Analytics Engineer Associate, DP-203 Azure Data Engineer Associate) 3-5 years – similar or related general experience in progressively more senior positions Technical Skills Strong proficiency in Microsoft Fabric platform components (Data Pipelines, Notebooks, Lakehouse, OneLake) Expertise in Apache Spark, data pipelines and data transformation frameworks Knowledge of data architecture and data modeling (Delta Lake architecture, Lakehouse design patterns, and medallion design pattern) Expertise in SQL for data querying, transformation, and pipeline development Proficiency in Python for data engineering, automation, and pipeline development Experience with software engineering for cloud platforms (Python, serverless) Experience with system integrations, APIs, and data pipelines across cloud and enterprise systems Experience working with CRM platform data and services (Salesforce preferred) Others may apply Operational Excellence Familiarity with DevOps practices including CI/CD pipelines, version control, and automation frameworks Experience implementing monitoring, logging, and alerting practices to ensure reliability and performance of data pipelines and services Commitment to engineering best practices including code quality, testing, documentation, and continuous improvement of data workflows Experience with scripting languages for automation and operational tasks Experience developing and maintaining automated testing frameworks for data pipelines and solutions Analytical Skills / Communication Skills Demonstrated ability to align technical deliverables with organizational strategy and business goals Strong troubleshooting, performance optimization, and problem-solving skills Strong verbal and written communication skills Ability to coordinate with technical and non-technical stakeholders effectively Thrives in a fast-paced, dynamic environments with shifting priorities Bilingualism (French/English) is highly preferred, with French being an asset due to the organizati
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.