Data Engineer (Business Data)

• Architect, design, and develop clean, high-performance datasets using modern tools like dbt and BigQuery, focusing on usability and scalability for analytical consumption.
• Be a key contributor to our domain-oriented data architecture, defining how core business entities (e.g., customers, payments) are modeled, governed, and exposed across the organization.
• Build and maintain robust batch and streaming data pipelines that transform raw data into trusted, analytics-ready assets to support both near real-time and traditional use cases.
• Collaborate closely with Analytics, Product, and Machine Learning teams to translate complex requirements into reusable, well-governed data models and contracts.
• Champion data quality, reliability, and documentation by implementing rigorous testing, validation, and monitoring practices.
• Leverage cutting-edge tools, including AI/agentic workflows, to accelerate development, enhance productivity, and improve data exploration and lineage.
• Participate in code reviews, contribute to improving engineering standards, and partner with platform teams to ensure our data solutions meet ambitious performance, cost, and scalability goals.

• 2+ years of experience working in data engineering, analytics engineering, or a related field.
• Experience building and maintaining data models and transformation pipelines (e.g., dbt or similar tools).
• Strong SQL skills and proficiency in Python (or similar language).
• Solid understanding of data modeling concepts (e.g., dimensional modeling, normalization, data warehousing patterns).
• Experience working with a cloud data warehouse (e.g., BigQuery, Snowflake, Redshift).
• Familiarity with orchestrators such as Airflow, GCC,  Dagster, Prefect (or similar tools).
• Basic understanding or exposure to streaming/event-driven systems (e.g., Pub/Sub, Kafka, Kinesis, Dataflow).
• Understanding of data quality, testing, and validation practices.
• Ability to work cross-functionally and communicate clearly with both technical and non-technical stakeholders.

• Experience in analytics engineering or working closely with analytics teams.
• Experience building or contributing to near real-time data pipelines.
• Familiarity with data governance, metadata management, or lineage tools.
• Experience using AI-assisted or agentic tools to improve development workflows.
• Experience in SaaS, fintech, or payments-related domains.

Compensation

Perks and Benefits

• 🩺 Comprehensive health and wellness benefits. Generous time off including a flexible vacation plan, a retirement savings program or pension plan matched to your local office, stock options for every full-time employee, parental leave and new parent support, annual healthy living credit, comprehensive medical and dental benefits, fertility and gender-affirming benefits dependent on your region, and more.
• 📚 Perks that matter. Including a Peer Recognition Program, an Employee Assistance Program, headphone credit, meaningful in-person gatherings to bring onsite and remote employees together, and more perks matched to your local cluster.
• 🌱 Working environments to help you thrive. Beautiful office spaces welcome you in Toronto, Amsterdam, and San Luis Potosi. If you don't have access to a FreshBooks office, you receive a home office credit to set up your home office.
• 🤗 Supportive peer group, mentors, and leaders. We care about each other across the organization and have programs to support this so everyone feels a strong sense of belonging, and believes in collective impact. 
• 🚀 Accelerated growth. Comprehensive company onboarding, career development through continuous coaching, training, and learning on the job.

About FreshBooks