BGIS is a leading commercial real estate firm dedicated to providing innovative solutions to our clients. We specialize in facilities management and are committed to staying at the forefront of technology and analytics in the real estate industry.
Job Description:We are seeking a skilled and experienced Data Engineer to join our dynamic and growing applied data analytics team. As a Data Engineer at BGIS, you will help us build our Analytics and AI Innovation Hub in Toronto. You will play an impactful and critical role in integrating and transforming our unmatched internal datasets with external data to drive insights, inform strategic decisions, and optimize our operations.
Responsibilities: Utilize your educational background in a quantitative field, such as computer science, mathematics, or engineering, to design, build, and maintain data pipelines and ETL processes. Leverage over five years of experience in data engineering, preferably with teams focused on machine learning, artificial intelligence, or data science. Design, build, and maintain robust data pipelines and ETL processes, ensuring data accuracy and accessibility for analysis and modeling. Develop and manage APIs for efficient data consumption, facilitating seamless integration and utilization of data across various platforms. Apply your passion for problem-solving to address complex data-related challenges, automate and optimize scalable data workflows. Maintain a strong understanding of data warehousing, cloud technologies, and big data solutions, constantly updating and improving our data infrastructure and knowledgebase. Communicate effectively across technical and business domains, collaborating with cross-functional teams to ensure the seamless integration of AI and data solutions. Participate in the development and deployment of AI and machine learning models, working closely with data scientists and analysts. Collaborate closely with data scientists and analysts, providing them with clean, structured analytical datasets necessary for advanced statistical modeling and machine learning. Demonstrate an aptitude for continuous learning, staying current with emerging technologies and best practices in data engineering, AI and analytics.
Qualifications: Bachelor's degree or higher in a quantitative field (Computer Science, Math, Engineering, etc.). Over five years of hands-on experience in data engineering, with some emphasis and familiarity with data preparation for AI and ML projects. A natural curiosity and enthusiasm for tackling challenging problems. Proficiency in data manipulation via SQL preferably using Snowflake Proficiency in data pipeline development, data modeling, data warehousing, and ETL processes. Familiarity with data visualization tools and techniques [Power BI, Tableau, Python libraries) Experience with data engineering technologies and data movement and transformation (e.g. Fivetran, DBT, Informatica, Dataiku, etc.) Excellent communication skills, with the ability to collaborate effectively with both technical and non-technical stakeholders. Proven track record of supporting delivery of actionable insights and solutions from complex data and analytic projects.
Why BGIS? Join a dynamic team at the forefront of data-driven decision-making in the commercial real estate industry, and at the creation of the BGIS Analytics and AI Innovation Hub. Collaborate with experts in the field and leverage cutting-edge technology. Competitive compensation package and opportunities for career growth. A supportive and inclusive work environment that values diversity and innovation. How to Apply:
If you are a dedicated Data Engineer with a passion for leveraging data to drive results and want to be part of a leading commercial real estate company, please send your resume and a cover letter outlining your relevant experience to [email here].
BGIS is an equal opportunity employer. We encourage candidates of all backgrounds to apply and if the qualifications seem a bit of a stretch, but the role sounds like an aspirational destination on your career roadmap, we’d like to hear from you in any case.