We are looking for a Data Engineer to join our growing team. Our system relies on a series of data pipelines for reporting and machine learning capabilities directly in the product, as well as for organizational decision making support. This role impacts our users and our business at a foundational level! You will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for cross-functional teams.
The ideal candidate is an experienced data pipeline builder who enjoys both evolving data systems and creating them from the ground up. The Data Engineering role could be the right role for you if you are excited by understanding what data means, enabling experimentation on models and visualizations, and ultimately productizing a maintainable and monitorable flow of information in our system to support a variety of team members and use cases.
At Properly, we are on a mission to make real estate customer-centric. We envision a future in which real estate transactions involve dramatically less friction and surprising simplicity and where Properly is the first choice of all Canadians throughout the entire experience of buying, selling and owning a home. Check out our CEO’s note on the culture we are trying to craft at Properly.
Properly is headquartered in Toronto. We have a foundation of experienced operators on our team (Uber, Wealthsimple, Wave, Ritual, Shopify, Blackberry, Facebook, etc.) and have raised over $115 million in funding from investors including FJ Labs, Prudence, Golden Ventures, iNovia Capital, AlleyCorp (Kevin Ryan), Silicon Valley Bank and others. We are an equal opportunity employer and celebrate diverse experiences and perspectives because they make our team more successful.
What you will do:
– Evolve, recreate and maintain data pipeline architectures
– Assemble large, complex data sets that can be used throughout our product and business
– Enable experimental and ad-hoc data-driven models and visualization for rapid feasibility and product planning.
– Identify, design, and implement internal process improvements: automating manual processes, improving data delivery, and re-designing infrastructure for greater scale
– Help us create product capabilities that fundamentally rely on data models
– Build analytics tools that use the data pipeline to provide insights into customer acquisition, operational efficiency and other key business performance metrics
– Work with stakeholders to assist with data-related technical issues and support their data infrastructure needs
What we’re looking for:
– 3+ years of experience in a Data Engineer role
– Experience working with a variety of databases and data systems (relational and non-relational, stream-based data processing, ETL systems, etc.)
– Advanced working SQL knowledge and experience working with relational databases
– Experience in a modern backend development environment (e.g. Python)
– Familiarity with DevOps type activities such as design for manageability and root cause analysis
– Strong analytic skills related to working with unstructured datasets
– Ability to develop processes supporting data transformation, data structures, and metadata to facilitate other team members successfully using data
– Experience supporting and working with cross-functional teams in a dynamic environment