Company Description
Assent is the leading solution for supply chain sustainability tailored for the world’s top-tier, sustainability-driven manufacturers. Hidden risks riddle supply chains, many of which weren’t built with sustainability in mind. That’s where we step in. With insights from experts, Assent is the tool manufacturers trust for comprehensive sustainability.
We are proud to announce that Assent has crossed the US$100M ARR milestone, granting us Centaur Status. This accomplishment, reached just 8 years following our Series A, makes us the first and only Certified B Corporation in North America’s SaaS sustainability industry to celebrate this milestone.
Our journey from $5 million to US$100M ARR in just eight years has been marked by significant growth and achievements. With our $350 million US funding led by Vista Equity Partners, we’re poised for even greater expansion and are on the lookout for outstanding team members to join our mission.

HYBRID WORK MODEL

At Assent, we proudly embrace a remote-first work model, valuing the flexibility and autonomy it provides our team. We also acknowledge the intangible benefits of occasional in-person workdays. For team members situated within 50 kms/31 miles of our five global offices in Ottawa, Eldoret, Penang, Columbus, Pune and Amsterdam, you can expect to come into the office at least one day a week. Similarly, those near our co-working spaces in Nairobi and Toronto are encouraged to work onsite once a month.
Job Description
At Assent, we’re committed to empowering the world’s most forward-thinking companies to deepen trust with their customers, supply chains, and communities. We’re looking for a curious, collaborative, and technically sharp Analytics Engineer to join our Revenue Analytics team—a strategic arm of Revenue Operations at the heart of our Go to Market organization.

This role is for a mid-career data professional who thrives on solving meaningful challenges in a modern data stack. You’ll be instrumental in scaling our data infrastructure, driving forward analytics maturity, and enabling predictive and generative insights that shape revenue strategy. With strong experience in GenAI, machine learning, and large language models, you’ll help shape how we extract more signals from our data.

• Engineer scalable data infrastructure – Design, build, and maintain robust, performant, and scalable data pipelines that integrate and transform data from across the business.
• Elevate data modeling – Architect clean, reliable data models that feed core business dashboards, analytics, and machine-learning applications.
• Bridge teams with insight – Collaborate with analysts, data scientists, revenue leaders, and stakeholders across GTM to deliver models and insights that drive better decisions.
• Champion data quality – Apply rigorous data validation and error-handling practices to ensure trust in our analytics layer.
• Optimize performance – Monitor and tune data pipelines for speed and reliability; anticipate growth and ensure systems are future-ready.
• Contribute to AI-driven innovation – Help incorporate GenAI tools and ML workflows that enhance forecasting, personalization, and operational insight across Revenue Operations.
• Lead and mentor – Support junior team members and elevate Assent’s data culture by sharing best practices and leading with empathy.
• Document and scale – Create approachable, scalable documentation and self-serve resources for data consumers across the company.
• Shape our data strategy – Stay on top of data engineering trends and bring your perspective to technical and architectural decisions.

Qualifications

We strongly value your talent, energy and passion. It will also be valuable to Assent if you have the following qualifications:

• 5+ years experience in data science, advanced analytics, or full-stack analytics roles, preferably in a B2B SaaS environment.
• Proven ability to translate data into strategy and balance statistical rigour with pragmatic decision-making.
• Advanced expertise in SQL, DBT, and modern data warehousing (Snowflake preferred).
• Strong proficiency in Python for analysis, modeling, and GenAI applications.
• Solid understanding of data infrastructure and pipeline orchestration, including CI/CD, Git, and Python scripting.
• Hands-on experience with Tableau (or equivalent BI tools); exposure to tools like AWS, Kubernetes, or orchestration frameworks is a bonus.
• A deep curiosity for how data drives growth, and how analytics can influence outcomes at every stage of the customer journey.
• Demonstrated exposure to generative AI, ML models, or LLMs, with practical experience in deploying them in analytics or business use cases.
• Demonstrated experience working cross-functionally with Sales, Marketing, CS, and Finance teams.
• A collaborative spirit, strong communication skills, and the ability to simplify complexity for non-technical audiences.
• A Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related discipline—or equivalent practical experience.

Additional Information

• Engineer scalable data infrastructure – Design, build, and maintain robust, performant, and scalable data pipelines that integrate and transform data from across the business.
• Elevate data modeling – Architect clean, reliable data models that feed core business dashboards, analytics, and machine-learning applications.
• Bridge teams with insight – Collaborate with analysts, data scientists, revenue leaders, and stakeholders across GTM to deliver models and insights that drive better decisions.
• Champion data quality – Apply rigorous data validation and error-handling practices to ensure trust in our analytics layer.
• Optimize performance – Monitor and tune data pipelines for speed and reliability; anticipate growth and ensure systems are future-ready.
• Contribute to AI-driven innovation – Help incorporate GenAI tools and ML workflows that enhance forecasting, personalization, and operational insight across Revenue Operations.
• Lead and mentor – Support junior team members and elevate Assent’s data culture by sharing best practices and leading with empathy.
• Document and scale – Create approachable, scalable documentation and self-serve resources for data consumers across the company.
• Shape our data strategy – Stay on top of data engineering trends and bring your perspective to technical and architectural decisions