The Opportunity 🚀

Carrot is seeking a Sr. Data Engineer to lead the evolution, reliability, and scalability of our modern data infrastructure across analytics, reporting, and business intelligence. In this role, you will architect, build, and maintain robust, automated data pipelines, orchestrate workflows, integrate diverse data sources, and partner with stakeholders across the business to deliver secure, compliant, high-quality data solutions.

Your work will span the full data lifecycle, from architecting resilient ETL/ELT pipelines and developing real-time and batch data integrations to automating reporting, reducing technical debt, and enabling advanced analytics. Sr. Data Engineers at Carrot are operational stewards and technical mentors, driving improvements in system maturity, cost efficiency, automation, and collaborative practices.

You will join our Data Engineering team, which develops and optimizes scalable data pipelines and cloud infrastructure to enable secure, automated reporting and analytics across Carrot. The team collaborates closely with Business Intelligence, Product, Finance, Legal, and Commercial partners to deliver reliable integrations and self-serve solutions that drive business insights and operational efficiency.

What You’ll Own 💼

In this role, you will:

• Architect, build, test, deploy, and maintain scalable, automated ETL/ELT pipelines using Python, dbt, and orchestration tools such as Prefect and Airflow
• Administer and optimize cloud-based data warehouse and lake platforms, including Snowflake, AWS (S3, Redshift), and Google Cloud, integrating new sources and tuning for performance and cost
• Orchestrate data workflows with custom scheduling, alerting, dependency management, monitoring, and error resolution
• Design and maintain secure external data flows through SFTP, Files.com, and APIs, with a focus on reliability and compliance
• Automate manual reporting and operational tasks, building robust, reusable pipeline components that reduce operational overhead
• Partner with backend product engineers to optimize production database schemas with analytics use cases in mind
• Strengthen data quality, lineage, governance, and documentation practices across key data domains
• Mentor teammates and reinforce best practices in version control, code review, and structured workflow management

What Success Looks Like 📈

In your first 12–18 months, you will have:

• Taken end-to-end ownership of core pipelines and integrations, with measurable improvements in reliability, data recency, and cost efficiency
• Automated high-effort manual workflows, reducing operational risk and freeing capacity for higher-value engineering work
• Delivered secure, compliant data integrations that stakeholders across the business trust for decision-making
• Strengthened observability across the platform, including monitoring, alerting, and incident response for critical data workflows
• Established yourself as a technical mentor and a go-to partner for Business Intelligence, Product, and cross-functional teams

About You ✨

You likely have:

• Expert-level proficiency in Snowflake, dbt, and Python for data modeling, transformation, pipeline development, and advanced analytics
• Advanced SQL skills for complex querying, large-scale data model design, and database optimization
• Proven experience architecting, building, testing, deploying, and maintaining scalable, automated ETL/ELT pipelines using modern orchestration tools such as Prefect and Airflow
• Hands-on administration of cloud-based data warehouse and lake platforms, including Snowflake, AWS (S3, Redshift), and Google Cloud
• A strong understanding of secure external data flows through SFTP, Files.com, and APIs, with a focus on reliability and compliance
• Mastery of version control (Git, GitHub) and structured workflow management (Jira) for code review, audit trails, and operational transparency
• A demonstrated ability to automate and simplify complex manual tasks, building robust, reusable pipeline components
• Dependability, adaptability, and a collaborative approach to engineering, thriving in dynamic and ambiguous environments

Nice to Have ⭐

While not required, we would be especially excited if you bring:

• Hands-on experience in startup or rapid-growth environments, delivering technical solutions under shifting priorities
• A background supporting business intelligence, analytics, and data science teams through large-scale integrations and multi-tenant reporting
• Familiarity with both batch and event-driven ingestion paradigms, including near-real-time pipelines built on Snowflake, dbt, and Python
• Experience automating operational, financial, or compliance-driven workflows within cloud data environments
• Exposure to audit, privacy, and compliance frameworks such as SOC 2, HIPAA, GDPR, ISO, and SOX, particularly in data governance and secure access controls
• Experience in regulated industries such as healthcare, healthtech, or SaaS

Why This Role Matters 🧡

Reliable data is the foundation of how Carrot operates, from the analytics that guide business decisions to the reporting our customers and partners depend on. The systems this role owns determine the accuracy, recency, and security of data used across the entire company.

As Carrot scales globally, the Sr. Data Engineer will make our data platform more automated, resilient, and cost-efficient, enabling teams across the business to move faster with data they trust. This work directly supports Carrot's mission of expanding access to fertility and family-building care worldwide.

Interview Process 🤝

We believe in a thoughtful and transparent interview process designed to create alignment for both candidates and our team.

For this role, candidates can expect:

1. Recruiter Screen — 30 minutes
2. Hiring Manager Interview — 30–45 minutes
3. Cross-Functional Panel Interviews — 45 minutes
4. Executive Leadership Conversation — 30 minutes
5. Hiring Manager Wrap-Up — 15 minutes

Throughout the process, we will share additional context about the team, business priorities, customer landscape, and what success looks like in this role.

Why Candidates Join Carrot 🌍

Carrot offers the opportunity to do meaningful work in service of a deeply human mission.

Highlights include:

• A mission-driven company focused on expanding access to fertility and family-forming care globally.
• A high-growth environment where leaders are empowered to shape strategy and drive impact.
• Competitive compensation, equity, and comprehensive benefits.
• Flexible Time Off and a culture that actively encourages employees to recharge.
• Comprehensive parental leave and family-forming benefits.
• A collaborative, inclusive, and values-driven culture.
• The opportunity to work alongside passionate, thoughtful teammates committed to improving healthcare outcomes worldwide.

Compensation:

Carrot offers a holistic Total Rewards package designed to support our employees in all aspects of their life inside and outside of work, including health and wellness benefits, retirement savings plans, short- and long-term incentives, parental leave, family-forming assistance, and a competitive compensation package. The starting base salary for this position will range from $145,000-$165,000. Actual compensation may vary from posted base salary depending on your confirmed job-related skills and experience.

Fraud and Security Notice: Please note that all communication regarding job opportunities at Carrot will come exclusively from an @get-carrot.com email address. If you receive messages from any other domain, please disregard them and report the incident to: [email protected]

A Note on AI

At Carrot, we believe AI can help us work smarter, move faster, and create more meaningful experiences for our members, customers, and each other. While not every role requires deep technical AI expertise, we value people who are curious, eager to learn, and excited to thoughtfully incorporate AI into their day-to-day work.

For some roles, AI fluency is a core requirement—and we'll call that out clearly in the qualifications. For everyone else, we're looking for people who embrace new ways of working, use AI responsibly to improve quality and efficiency, and continue to learn as the technology evolves.