Remote opportunity at
CarrotSr. Data Engineer
Carrot is seeking a Sr. Data Engineer to lead the scalability, reliability, and evolution of its modern data infrastructure across reporting, business intelligence, and analytics. Operating…
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About This Role
Carrot is seeking a Sr. Data Engineer to lead the scalability, reliability, and evolution of its modern data infrastructure across reporting, business intelligence, and analytics. Operating as a global fertility and family care platform, Carrot relies on intelligent care orchestration to offer clinical guidance to millions of members across 195 countries. In this position, you will own the entire data lifecycle by designing automated ETL/ELT pipelines, maintaining cloud-based data warehouses,…
Job Description
Carrot is seeking a Sr. Data Engineer to lead the scalability, reliability, and evolution of its modern data infrastructure across reporting, business intelligence, and analytics. Operating as a global fertility and family care platform, Carrot relies on intelligent care orchestration to offer clinical guidance to millions of members across 195 countries. In this position, you will own the entire data lifecycle by designing automated ETL/ELT pipelines, maintaining cloud-based data warehouses, and collaborating with cross-functional partners in finance, product, commercial, legal, and business intelligence.
This role suits an experienced engineer who excels at managing secure data flows, reducing operational overhead, and mentoring teammates on version control and structured workflows. You will utilize tools like Python, dbt, Snowflake, and workflow orchestration platforms to build robust, reusable data integrations while strengthening observability and data governance practices across the organization. Carrot offers a total rewards package that includes a competitive base salary alongside health and wellness benefits, retirement savings plans, parental leave, and flexible time off.
Responsibilities
- Design, build, deploy, test, and maintain scalable and automated ETL/ELT pipelines utilizing Python, dbt, Airflow, and Prefect
- Manage and tune cloud-based data warehouses and data lakes including Snowflake, Google Cloud, and AWS services such as Redshift and S3
- Configure data workflows featuring custom scheduling, monitoring, alerting, dependency management, and error handling
- Maintain secure external data integrations across APIs, Files.com, and SFTP with an emphasis on compliance and reliability
- Automate manual reporting processes and operational workflows to construct reusable pipeline components
- Collaborate with backend product engineers to refine production database schemas for analytical requirements
- Promote best practices surrounding data lineage, quality, governance, and documentation across major data domains
- Provide technical mentorship to teammates regarding code reviews, version control, and workflow management
Requirements
- Expert proficiency in Python, dbt, and Snowflake for pipeline development, data modeling, transformation, and advanced analytics
- Advanced SQL expertise for complex querying, database optimization, and large-scale data model creation
- Demonstrated experience designing, building, testing, deploying, and maintaining automated ETL/ELT pipelines with modern orchestration platforms like Airflow and Prefect
- Hands-on administrative experience with cloud data lakes and warehouses including Google Cloud, Snowflake, and AWS
- Solid understanding of secure external data integration methodologies via APIs, Files.com, and SFTP
- Mastery of Git, GitHub, and Jira for version control and structured workflow management
- Proven capability to simplify and automate complex manual tasks through reusable pipeline components
Qualifications
- Hands-on background working in rapid-growth or startup environments under shifting priorities
- Experience supporting data science, analytics, and business intelligence teams via large-scale integrations and multi-tenant reporting
- Familiarity with event-driven and batch ingestion paradigms, including near-real-time pipelines utilizing Python, dbt, and Snowflake
- Prior exposure to automating financial, compliance-driven, or operational workflows within cloud environments
- Knowledge of privacy, audit, and compliance frameworks such as SOC 2, HIPAA, GDPR, SOX, and ISO in relation to data governance and access controls
- Background operating in regulated domains like SaaS, healthcare, or healthtech
Core Skills
Benefits
- Competitive base salary ranging from USD 145,000 to 165,000 per year
- Total rewards package covering health and wellness benefits and retirement savings plans
- Short- and long-term incentives alongside family-forming assistance and parental leave
- Flexible Time Off
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
What is the salary for the Sr. Data Engineer role?
The starting base salary for this position ranges from USD 145,000 to 165,000 per year, with actual compensation varying based on confirmed job-related skills and experience.
What is the remote work policy for this job?
The posting indicates that the position is remote.
What employment type is this role?
This position is a full-time role.
What tools and technologies are required for this position?
Candidates must have expert proficiency in Snowflake, dbt, and Python, advanced SQL skills, hands-on experience with cloud platforms like AWS and Google Cloud, and familiarity with orchestration tools such as Airflow and Prefect.
Sample Interview Questions
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