Senior Data Engineer, Data Platform

EvenUp is on a mission to close the justice gap using technology and AI. We empower personal injury lawyers and victims to get the justice they deserve. Our products enable law firms to secure faster settlements, higher payouts, and better outcomes for victims injured through no fault of their own in vehicle collisions, accidents, natural disasters, and more.

We are one of the fastest-growing vertical SaaS companies in history, and we are just getting started. EvenUp is backed by top VCs, including Bessemer Venture Partners, Bain Capital Ventures, SignalFire, and Lightspeed. We are looking to expand our team with talented, driven, and collaborative individuals who seek to have a lasting impact. Learn more at www.evenuplaw.com.

Location & Work Model

This is a hybrid role, with an expectation of being in one of our Toronto office at least three days per week.

About the Team

The Data & Analytics team at EvenUp plays a critical role in driving data-informed decision-making across the organization. We partner closely with Product, Engineering, Operations, and Executive teams to uncover insights, build scalable data solutions, and enable a culture of data-driven decision-making and continuous improvement.

Our team owns the full data lifecycle — from foundational data modeling and reporting to advanced analytics, experimentation, and forecasting. We’re focused on building a scalable, reliable data platform that powers fast, actionable insights across the business.

Responsibilities

• Build and scale the data platform that powers analytics, experimentation, and business intelligence across the organization
• Design and maintain robust, well-documented ELT/ETL pipelines and reusable data models
• Partner cross-functionally with Product, Engineering, Operations, and Analytics teams to translate business needs into scalable data solutions
• Own the design and implementation of data pipelines supporting product instrumentation, reporting, and experimentation
• Establish and maintain high standards for data quality, reliability, governance, and observability
• Contribute to a strong data engineering culture through mentorship and best practices

What You’ll Do

• Data Platform Development: Build and maintain scalable data pipelines and infrastructure using tools such as dbt, Airflow or Dagster, and BigQuery, Snowflake, or similar technologies. Ensure reliability, documentation, and performance at scale.
• Cross-Functional Collaboration: Partner closely with Product Managers, Data Scientists, ML Engineers, Software Engineers, and Operations stakeholders to understand data requirements and deliver high-quality, scalable solutions.
• Data Modeling & Architecture: Design dimensional models, define clear source-of-truth metrics, and drive improvements in data architecture with a focus on usability, governance, and scalability.
• Data Quality & Observability: Improve data reliability by implementing testing, monitoring, and observability best practices to reduce human error and ensure trust in data outputs.
• Analytics & Reporting Enablement: Support business intelligence and experimentation efforts by building data models and enabling reporting and dashboarding solutions using tools such as Looker, Tableau, or Metabase.
• Team Growth & Mentorship: Mentor engineers and analysts on data modeling standards, tooling, and engineering best practices while helping shape a strong, collaborative data culture.

What We Look For

• 4+ years of experience as a Data Engineer or Software Engineer, ideally in product-focused, high-growth environments
• Strong proficiency in Python for data wrangling, orchestration logic, and navigating application codebases
• Strong proficiency in SQL and experience using transformation tools such as dbt to build reusable data models
• Experience designing dimensional models and defining clear, trusted business metrics
• Experience building scalable, reliable data pipelines in modern cloud environments
• Familiarity with data warehouse technologies such as BigQuery or Snowflake and orchestration tools such as Airflow or Dagster
• Experience enabling reporting and visualization solutions using dashboarding tools (e.g., Looker, Tableau, Metabase)
• Strong communication and collaboration skills when working with cross-functional stakeholders
• High attention to detail, structured thinking, and a bias toward action in fast-paced environments
• Leadership potential with interest in mentoring others and shaping data engineering best practices

Bonus (Nice to Have)

• Experience working as a product software engineer
• Experience in the legal domain
• Experience processing unstructured data or working with document-processing systems
• Experience supporting experimentation frameworks or product analytics initiatives

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