Job Description REQUIREMENTS - 3+YOE in Data Engineering and working with GCP, GCP Big Query - Knowledge on Data warehouse - Experienc working with Data forms - Excellent data engineering skills including expert SQL, data modeling, and query optimization - Strong experience with big data stack (Spark, PySpark, Hadoop, HIVE, BigQuery, Pub/Sub) in building scalable ETL pipelines - Excellent programming skills (Python) including production level coding techniques (testing, OOP structures, optimization, etc) - Data visualization and dashboarding experience - Great at debugging, troubleshooting, designing, and implementing solutions to complex technical issues - Aptitude to independently learn new technologies, prototype, and propose solutions - Advanced English level RESPONSIBILITIES - Design a cloud-based data warehouse using BigQuery to support analytical workloads. Define fact and dimension tables, apply appropriate partitioning and clustering strategies, and document the data model. - Build a scalable ETL pipeline using PySpark on GCP that ingests raw data, applies transformations, and writes curated data to BigQuery. Implement error handling, logging, unit tests, and modular OOP-based code. - Design and implement a real-time data ingestion solution using Pub/Sub and Dataflow to process streaming events and store aggregated results in BigQuery. - Use Dataform to build, version, and manage SQL-based transformations in BigQuery. Define dependencies, apply data quality assertions, and automate pipeline execution. - Create a dashboard using BigQuery as the data source (e.g., Looker or Looker Studio). Optimize queries for performance and explain metrics, KPIs, and design decisions to stakeholders. About Capgemini Group Capgemini is a global leader in partnering with companies to transform and manage their business by harnessing the power of technology. The Group is guided everyday by its purpose of unleashing human energy through technology for an inclusive and sustainable future. It is a responsible and diverse organization of over 300,000 team members in nearly 50 countries. With its strong 50-year heritage and deep industry expertise, Capgemini is trusted by its clients to address the entire breadth of their business needs, from strategy and design to operations, fueled by the fast evolving and innovative world of cloud, data, AI, connectivity, software, digital engineering and platforms. What you will love about working with us: - At Capgemini we’re always looking ahead. - We reimagine possibilities, and we innovate with technology to bring ideas to life. - We encourage flexibility in how, when, and where people get their work done, allowing a better work-life balance, and greater empowerment. - They partner with their managers to find an arrangement that works best for their role and their circumstances. - We offer game-changing programs to accelerate the growth of our people and the development of their expertise. What you need to know about what we offer: - Excellent compensation and benefits - Career path, trainings and real growth opportunities - Engaging and challenging projects. - Excellent work environment and culture. - Open and Effective management. - Highly professional and collaborative teams. At Capgemini Mexico, we aim to attract the best talent and are committed to creating a diverse and inclusive work environment, so there is no discrimination based on race, sex, sexual orientation, gender identity or expression, or any other characteristic of a person. All applications welcome and will be considered based on merit against the job and/or experience for the position.

Posting Reason: New Position Location: Main Campus Academic Period: 2026 Spring-Summer Semester Faculty: Faculté des sciences sociales / Faculty of Social Sciences Academic Unit: École de psychologie \\ School of Psychology Course Title: The Psychology of Adolescence Course Code: PSY3105 Section: E00 Course Description: Physical, emotional, social, moral and intellectual development of the adolescent. Problems in the development of personal, social and sexual maturity. Current research in the psychology of adolescence. Course Component: Lecture Posting limited to: Professeur à temps-partiel régulier / Regular Part-Time Professor Date Posted (YYYY/MM/DD): 2026/04/16 Applications must be received BEFORE (YYYY/MM/DD): 2026/04/23 Expected Enrolment: 147 Approval date: 2026/04/16 Number of credits: 3 Work Hours: 39 Hourly Rate: Enseignement / Teaching: $239.47 (2024-2025)The academic year starts on September 1 and ends on August 31. These rates do not included vacation pay nor statutory pay. These rates will be applied until a new collective agreement is ratified. Retro will be paid after the ratification. Course type: B Posting type: Irrégulier / Irregular Language of instruction: Anglais | English Competence in second language: Passive Course Schedule: Mardi | Tuesday 13:00-16:00 Jeudi | Thursday 13:00-16:00 - This course is offered online. Requirements: Ph.D. in Psychology / Advanced knowledge of the course content area Additional Information and/or Comments: An acceptable level of education and/or experience could be viewed as being equivalent to the educational required and/or demonstrated experience. If you are invited to continue the selection process, please notify us of any adaptive measures you might require. Information you send us will be handled respectfully and in complete confidence. Employees are required under provincial law to successfully complete all mandatory legislated training. The list of training may be modified by provincial law. The hiring process will be governed by the current APTPUO collective agreements; you can click here for the main unit, here for the OLBI unit, or here for the Toronto/Windsor unit to find out more. The University of Ottawa embraces diversity and inclusion in the workplace. We are passionate about our people and committed to employment equity. We foster a culture of respect, teamwork and inclusion, where collaboration, innovation, and creativity fuel our quest for research and teaching excellence. While all qualified persons are invited to apply, we welcome applications from qualified Indigenous persons, racialized persons, persons with disabilities, women and LGBTQIA2S+ persons. The University is committed to creating and maintaining an accessible, barrier-free work environment. The University is also committed to working with applicants with disabilities requesting accommodation during the recruitment, assessment and selection processes. Applicants with disabilities may contact vra.affairesprofessorales@uottawa.ca to communicate the accommodation need. All qualified candidates are encouraged to apply; however, Canadians and permanent residents will be given priority. Prior to May 1, 2022, the University required all students, faculty, staff, and visitors (including contractors) to be fully vaccinated against Covid-19 as defined in Policy 129 – Covid-19 Vaccination. This policy was suspended effective May 1, 2022 but may be reinstated at any point in the future depending on public health guidelines and the recommendations of experts.

• Imagine shaping the future of how data drives business decisions and AI innovation. • Build, maintain, and optimize end-to-end data pipelines using dbt, Python, PySpark, Polars, and SQL. • Operate and enhance our AWS data infrastructure, including Glue, Athena, S3, and supporting tools. • Design and evolve Apache Iceberg tables, managing schema evolution, partitioning, compaction, and efficient storage. • Drive data quality, observability, lineage, and monitoring across the entire data platform. • Translate business and analytical needs into scalable, maintainable, and high-performing data solutions. • Collaborate with data scientists, analysts, engineers, and product teams to deliver clean, trusted datasets and APIs. • Contribute to the ongoing evolution of our data mesh, developing new patterns, enhancements, and architecture improvements. • Build AI/ML-ready data environments and datasets that enable intelligent products and predictive insights. • Document systems, design decisions, and processes to ensure clarity, consistency, and smooth onboarding.

The Data Engineer is responsible for developing and maintaining data pipelines to support data ingestion, transformation, and integration within a scalable data platform. This role ensures that data from multiple sources is processed efficiently, securely, and with high quality standards. Responsibilities - Develop and maintain data ingestion pipelines from multiple sources - Build ETL/ELT processes for data transformation - Integrate structured and unstructured data into data platforms - Implement incremental and automated data ingestion processes - Ensure data quality through validations and monitoring - Perform data cleaning and normalization tasks - Optimize pipelines for performance and scalability - Document data pipelines and data structures - Collaborate with cross-functional teams to support data initiatives Requirements - Bachelor’s degree in Computer Science, Engineering, or related field - Experience in data engineering or data pipeline development - Knowledge of ETL/ELT processes and data integration concepts - Experience with cloud-based data platforms (AWS or similar) - Experience working with APIs and database integrations - Proficiency in SQL and scripting languages (Python or similar) - Familiarity with distributed data processing frameworks Nice to Have - Experience with AWS data services - Knowledge of infrastructure as code tools - Familiarity with data lake architectures - Experience with Spark or similar technologies - Experience with data pipeline orchestration tools Soft Skills - Analytical thinking - Problem-solving skills - Collaborative mindset - Attention to detail