Data Engineer

at  Quandri

WE’RE QUANDRI. WE TRAIN INTELLIGENT ROBOTS TO POWER THE MODERN INSURANCE BROKERAGE AND AGENCY. WE’RE ON A MISSION TO UNLOCK 10,000,000 HOURS OF REPETITIVE WORK OVER THE NEXT THREE YEARS, SO THAT TIME CAN BE USED FOR MORE VALUABLE AND MEANINGFUL ENDEAVORS.

Every year, billions of hours are wasted on repetitive and manual work. This is work that can and should be automated, but has been overlooked. Quandri is building an AI robotics platform to fix this for the insurance industry.
Our robots enable insurance brokerages and agencies to automate many of their most time-consuming and repetitive processes. These software robots can be deployed into a customer’s existing software systems and work within their processes similar to how a person would, but at lightning speed and indefinitely.
We’ve begun by tackling massive problems around repetitive and high-volume work in the P&C insurance industry in North America, and have no shortage of product and geographic expansion opportunities over the next few years where this technology can have an even larger impact. We’ve raised venture capital from top US and Canadian investors to help us achieve our mission, and are now scaling the company to achieve this.
We saw 8x ARR growth last year and are aiming for 3x this year, making Quandri one of the fastest growing technology companies in Canada. We have won a few awards, and have already made a big impact on the insurance industry. However, what matters most is making our customer’s lives better one automated process at a time. We want you to be a critical part of that journey! We’re a hybrid company, with ⅔ of our team in Vancouver and the rest distributed. For those in Vancouver, we have an office in Gastown that we expect people to be at three days a week. We understand both the advantages of some flexibility around personal lives, and the positive interpersonal effects of in-person collaboration.

BASIC QUALIFICATIONS

• Minimum Experience: At least 3 to 6 years of non-internship professional data engineering experience. Demonstrated ability in taking responsibilities in data engineering projects.
• Data Warehousing Solutions: Demonstrated experience with owning the maintenance and implementation of databases and backends with a focus on efficient data management and integration of system components.
• Programming Languages: Proficiency in Python (Preferred) and SQL, with familiarity in Java, C#, Go, or Rust being beneficial.
• Cloud Computing Platforms: Hands on experience with cloud platforms like AWS, Azure, or GCP.
• DevOps Practices and Tools: Basics of Docker and Kubernetes and an understanding of CI/CD practices for data engineering.
• Data Pipeline Orchestration Tools: Experience with tools like Apache Airflow, Luigi, or AWS Step Functions for managing and automating data pipelines.
• Data Visualization Tools: Proficiency in data visualization tools such as Tableau, Power BI, or even Python libraries like Matplotlib and Seaborn for effective data presentation and storytelling.
• Best Practices: Knowledge of best practices in ETL and for maintaining scalable, secure, and efficient data infrastructures.
• Agile and Scrum Methodologies: Practical experience of Agile development principles, Scrum, or Kanban.
• Version Control: Competence in using Git, including branching strategies and collaborative development workflows.
• Analytical Skills: Strong problem-solving abilities with an understanding of algorithms and data structures.
• Security Knowledge: Awareness of cybersecurity fundamentals, secure coding practices, and common security vulnerabilities.

PREFERRED QUALIFICATIONS

• A Bachelor’s degree in Computer Science, Information Technology, Computer Engineering, or related IT discipline; or relevant experience equivalent to such a degree.
• A candidate who shows solid proficiency in Python and SQL. The ideal applicant should have experience in developing solutions using Python and demonstrate a good understanding of its capabilities and best practices. The ability to write clean, efficient, and well-documented code in Python is desirable.

YOUR ROLE

At Quandri, we’re embarking on an exciting journey to transform the workforce through automation, powered by AI and robotics. We’re looking for a Data Engineer to join our team. You will not only be our inaugural Data Engineer but also a trailblazer, setting the stage for our data engineering protocols and infrastructure. This position offers the rare opportunity to mold and influence our data engineering landscape from the ground up.
In this position, you’ll be instrumental in interpreting project visions and translating them into effective, scalable system architectures. Your role will be diverse, involving tasks such as breaking down complex projects, understanding the synergy between various software components, and enhancing the technical robustness and health of our infrastructure.
You will leverage your skills in writing scalable code, effective communication, and crafting supportive technical documentation. You will also spearhead system maintenance and enhancements, ensuring the scalability and resilience of our platform. Collaborating closely with our Chief Architect, DevOps Engineer, and Head of Data, you will be supported by a team of experts, enabling you to navigate challenges and innovate with confidence.
We are seeking more than just a skilled engineer; we are looking for a pioneer who is eager to make a substantial impact. The ideal candidate thrives in a fast-paced setting, is deeply curious about our product and industry, and is enthusiastic about tackling the challenges we face. If you are ready to be a part of a dynamic team and drive significant advancements in data engineering at Quandri, we look forward to welcoming you aboard.

KEY RESPONSIBILITIES

• Develop, test, and maintain scalable data pipelines, ensuring alignment with business needs and industry standards.
• Integrate modern data management and software engineering technologies into established data frameworks. Establish routines for data extraction and transformation.
• Develop and maintain cloud databases in collaboration with our Cloud Architect. Improve the processes for data retrieval and optimize analytics dashboards for enhanced insights.
• Collaborate with business and analytics teams to refine data models, enhancing the efficacy of business intelligence tools and supporting data-driven decision-making.
• Implement quality control measures for data accuracy and integrity, employing strategies for error detection, correction, and process optimization.
• Work closely with data scientists, architects, and business units to align on data requirements. Communicate technical concepts to non-technical stakeholders effectively.
• Adhere to and enforce data management and security policies. Safeguard data transfer and integration within new systems.
• Continually update knowledge on emerging data technologies and trends. Proactively seek opportunities to enhance existing data systems and practices.
• Identify and resolve issues in infrastructure and application deployment, focusing on system stability and efficiency.
• Guide and mentor software engineers in data best practices. Lead through example, emphasizing excellence and collaborative work.