About Karbon
Karbon is the global leader in practice management software for growth-minded accounting firms. We provide an award-winning, highly collaborative cloud platform that streamlines work and communication, enabling the average accounting firm using Karbon to save 18.5 hours per week, per employee.
We have customers in 34 countries and have grown into a globally distributed team, with our people based throughout the US, Australia, New Zealand, Canada, the United Kingdom, and the Philippines. We are well-funded, ranked #1 on G2, have a fantastic team culture built on our values, are growing rapidly, and making a global impact.
Role Overview
We're seeking a mid-level Data Engineer to join our growing data team and drive customer-focused analytics initiatives. This role will own end-to-end data infrastructure while maintaining a strong focus on understanding and improving customer outcomes. You'll work closely with Customer Success, GTM, and Product teams to ensure our data systems enable actionable insights that drive customer retention and growth.
About the Role
Data Infrastructure \& Engineering (60%)
Design, build, and maintain scalable data pipelines using Snowflake, dbt, Fivetran, Stitch and Snowpipe
Implement real-time streaming architectures to reduce data latency from hours to minutes
Manage schema evolution and data migrations for critical business entities
Optimize data warehouse performance and cost efficiency
Build robust monitoring and alerting systems for data pipeline health
Ensure data quality, reliability, and governance across all systems
Customer-Focused Analytics (20%)
Develop analytics frameworks to measure customer success and product adoption
Build cohorted churn analysis models to identify retention patterns
Create performance metrics that correlate with customer outcomes
Partner with Customer Success team to understand data needs for customer health scoring
Support implementation team analytics to improve onboarding effectiveness
Cross-Functional Collaboration (10%)
Work with Product teams to instrument new features and track adoption
Collaborate with Customer Success on quarterly business review data requirements
Support sales and marketing teams with pipeline and funnel analytics
Document data models and maintain technical specifications
Mentor junior team members and contribute to best practices
AI-Enabled Analytics \& Tooling (10%)
Leverage AI-powered tools to improve development velocity, data quality, and customer insight generation across the analytics stack.
Use AI-assisted development tools (e.g., GitHub Copilot, Cursor, or similar) to accelerate SQL, dbt, and pipeline development while maintaining high standards for accuracy and maintainability
Apply AI-supported techniques for anomaly detection, data quality monitoring, and schema exploration in customer and product data
Enable AI-driven insights within analytics platforms to surface trends, risks, and early indicators of churn or onboarding friction
Partner with analytics and business teams to support emerging predictive and proactive customer analytics use cases
About You
3-5 years of experience in data engineering or analytics engineering roles
Strong proficiency in SQL and experience with modern data warehouses (Snowflake preferred)
Experience with dbt for data transformation and modeling
Familiarity with streaming data architectures and real-time processing
Understanding of SaaS metrics (churn, retention, product adoption, customer health)
Experience working with customer-facing teams (Customer Success, Implementation, Product)
Strong problem-solving skills and attention to data quality
Preferred Qualifications
Experience in B2B SaaS or professional services software environments
Knowledge of customer success platforms and methodologies
Familiarity with event tracking and product analytics tools
Experience with cloud platforms (AWS/Azure) and infrastructure as code
Understanding of accounting/finance business processes (bonus)
Previous experience supporting non-technical stakeholders with data needs
Databricks experience strongly preferred - our data platform will be migrating from Snowflake to Databricks in the coming months
Technical Stack
Data Warehouse: Snowflake (transitioning to Databricks)
Transformation: dbt (data build tool)
ETL: Fivetran, Stitch
Orchestration: Snowpipe, scheduled jobs
Analytics Platform: Netspring
Collaboration: Linear, Slack, documentation tools
Why Work with Karbon?
Up to 5 weeks paid vacation per year
Strong benefits package including fully employer paid:
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Medical, prescription and paramedical
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Dental
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Vision
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Life insurance
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$500 a year healthcare spending account
Flexible work hours
Working from home allowance
Generous parental leave
Work with (and learn from) an experienced, high-performing team
Be part of a fast-growing company that firmly believes in promoting high performers from within
A collaborative, team-oriented culture that embraces diversity invests in development and provides consistent feedback
Karbon embraces diversity and inclusion, aligning with our values as a business. Research has shown that women and underrepresented groups are less likely to apply to jobs unless they meet every single criteria. If you've made it this far in the job description but your past experience doesn't perfectly align, we do encourage you to still apply. You could still be the right person for the role!
We recruit and reward people based on capability and performance. We don't discriminate based on race, gender, sexual orientation, gender identity or expression, lifestyle, age, educational background, national origin, religion, physical or cognitive ability, and other diversity dimensions that may hinder inclusion in the organization.
Generally, if you are a good person, we want to talk to you.
If there are any adjustments or accommodations that we can make to assist you during the recruitment process, and your journey at Karbon, contact us at people.support@karbonhq.com for a confidential discussion.
At this time, we request that agency referrals are not submitted for this position. We appreciate your understanding and encourage direct applications from interested candidates. Thank you!