Data Engineer

About the job
NOTE: Hybrid work model, 2 days/week in Toronto, Ontario office.

TYPE: 6-Month Contract

SKILLS: Data Engineer, LLM, RAG, ML, AI, Azure AI, OpenAI, Power BI, Microsoft Fabric, Databricks, Copilot Studio, Python, C#, Java, Data Warehouse, ETL, Data Modeling, SaaS, Azure, AWS, GCP, Git

INDUSTRY: Investments, Bank

DESCRIPTION:

You will collaborate with Middleware/Product/Data Engineering, Data Scientists, and business stakeholders to deliver well-managed and supported AI + Analytical Platforms within the organization. This includes technologies like Generative AI/large language models (LLMs), agent-based and RAG systems, Power BI/Fabricand Machine learning. Your role will be to maintain, manage and enhance these platforms: including continuous improvement, refinement and exploration of new features to meet evolving business needs and leverage the latest technological advancements.

You’ll join the Data, Analytics & AI team, a multidisciplinary group of data scientists, data analytics specialists, data engineers, and data visualization experts. Collaborating closely in this environment, you’ll support the development of Generative AI applications and the delivery & management of Analytical & AI technologies.You’ll also work directly with our Middleware & Product engineering team, Product Owners, Enterprise Architects, Software developers, and internal business team clients (Capital Markets, Quants, Private Investment, and more).You will report to Senior Analytical Technology Manager, Data Science & Advanced AnalyticsSupporting and maintaining the Analytical & AI platforms, which include Azure AI Services (OpenAI), Power BI/Fabric, Databricks, and Copilot Studio.Help with driving user adoption and best practices through training and support, fostering a community of practice, ensuring continuous improvement, and exploring and experimenting with innovative ways to leverage these tools for maximum business value:Facilitate support requests by managing their intake process: organizing requests, prioritizing, and addressing issuesWorking with cutting-edge technology to build AI solutionsMonitoring and maintaining the health, performance, and cost of the technologies to identify areas for improvement and automationAddressing inquiries from various roles in the business, offering guidance on effective technology utilization, such as AI and Analytical technologiesConducting training sessions and creating materials, assisting with onboarding and setup, and developing/maintaining user documentation and knowledge resources.Be able to research independently for potential solutions to problems encountered.Develop and implement use cases that demonstrate the value of these technologies in driving business outcomes

REQUIREMENTS:

A degree in Computer Science, Physics, Mathematics, Statistics, Engineering, Data Analytics or equivalent experience and certifications.Strong customer service skills and a drive to provide effective and timely support and resolution of issues with professionalism.Ability to troubleshoot complex problems involving multiple systems and components.Strong desire to work in a team-based and collaborative environment.Proven ability to quickly learn and understand complex subject matters.Experience in writing documentation and procedure manuals for various audiences.Problem-solving mindset: Tackle complex challenges, identify and resolve technical roadblocks, and contribute to innovative solutions.Accountable for work, investing time in research, learning, and practice to become an expert in our offeringsWillingness to learn new technologies and adapt to a rapidly evolving data landscape.Proficiency in one or more programming languages like Python, C#, JavaStrong communication skills, ability to articulate thoughts / ideas to effectively collaborate with a variety of teams from both investments and technology.Proven track record of staying current with technologyUnderstanding of machine learning concepts and experience building data pipelines to support ML/AIworkloads is a plus.Basic understanding of data warehousing, ETL processes, and data modelingconcepts.Basic knowledge of SQLor other query languages for data exploration and troubleshooting.Working knowledge of low-code SaaS and Cloud Data PlatformsKnowledge in a scripting languagefor automating administrative tasks and workflows.Public Cloud Technical Expertise such as Azure, AWS and GCPUnderstanding of DevOpsprinciples and practices, including automation, monitoring, and continuous delivery.Experience in industry or an academic setting of:

Technical support, technical consulting experience, or information technology experienceExperience and demonstrated expertise in managing and supporting SaaS or PaaSDemonstrated experience with communication and interpersonal skills, including written and presentational, with the ability to work and engage with a diverse range of customers and stakeholders at all levels.Experience in Cloud computingExperience with version control systems (e.g., Git) and CI/CD pipelines.Experience working in an Agile environment.Experience documenting business processes, gathering service requirements from diverse groups of stakeholders, to inform current and future service provision.Experience / Knowledge with surrounding technologies such as SharePoint, OneDrive, Teams, and wider M365applications.Experience and knowledge of foundational Generative AI principles such as prompt engineering, RAG, finetuning, etc and frameworks will be an asset.