Data Engineer

Role overview

The Data Engineer helps evolve the reliability and scalability of Carrot’s modern data platform across analytics, reporting, and business intelligence. They build and maintain robust, automated data pipelines and partner with cross-functional stakeholders to deliver secure, compliant, high-quality data solutions.

This role is hands-on across the data lifecycle—contributing to resilient ETL/ELT pipelines, real-time and batch integrations, and workflow orchestration—while steadily improving automation, cost efficiency, and documentation quality.

You will improve the reliability and scalability of Carrot’s data platform, reduce manual operational risk through automation, and enable stakeholders with secure, high-quality data—while growing your scope toward deeper ownership and technical leadership over time.

Key responsibilities

• Data pipeline development and operations: Build, test, deploy, monitor, and iterate on scalable ETL/ELT pipelines using platforms such as dbt and Fivetran; contribute to standard workflows (e.g., member engagement, finance/billing reports) and support ad hoc reporting needs.
• Warehouse and lake stewardship: Contribute to the design and continuous improvement of Snowflake and related cloud data platforms (AWS/GCP), including source integrations, performance tuning, and cost optimizations.
• Workflow orchestration and integrations: Develop auditable orchestration flows with tools like Prefect or Airflow; integrate with services such as S3, SFTP, APIs, and Files.com: Next-Generation MFT, SFTP File Sharing ; implement robust alerting, retries, and monitoring.
• Infrastructure optimization: Identify opportunities to improve pipeline speed, reliability, and cost; help refactor legacy processes, reduce manual steps, and document changes for scale and reuse.
• Partner- and stakeholder-facing deliverables: Support automated data integrations and exports (e.g., eligibility feeds, payroll/tax/billing files) with finance, product, legal, and commercial teams; help enforce data specs and secure handling of sensitive information.
• Change management and auditability: Follow best practices for Git/GitHub, code reviews, testing, Jira workflows, audit-trail documentation, and exception logging; uphold InfoSec and compliance standards across the data lifecycle.
• Analytics enablement: Help design modular, well-documented data models and marts (dbt/Snowflake) that enable BI and data science use cases (e.g., segmentation, provider matching, engagement analytics).
• Incident participation and support: Participate in on-call or escalation routines for high-impact data incidents; assist with root-cause analysis, remediation, and clear stakeholder communications.
• Process automation: Codify business rules and automate recurring cycles (e.g., monthly finance handoffs, audit logs) to reduce manual intervention and operational risk.
• Data security and governance: Implement privacy-conscious practices such as masking and de-identification; contribute to safe, compliant access across the stack and external data exchanges.

Minimum qualifications

• Proficiency with Snowflake, dbt, and Python for data modeling, transformations, and pipeline development in production environments.
• Strong SQL skills for complex querying and performance optimization across large datasets.
• Experience building and maintaining automated ETL/ELT pipelines using orchestration tools such as Prefect or Airflow, including alerting, dependency management, and retries.
• Hands-on exposure to cloud data platforms (e.g., Snowflake, AWS S3/Redshift, Google Cloud) and integrating new data sources at scale.
• Understanding of secure external data flows via SFTP, Files.com: Next-Generation MFT, SFTP File Sharing, and APIs, with attention to reliability and compliance requirements.
• Comfort with Git/GitHub and Jira for version control, code reviews, and operational transparency in a team setting.
• Track record of automating manual workflows and creating reusable components that reduce operational overhead.
• Collaborative, dependable working style with adaptability in dynamic environments and clear communication with technical and non-technical partners.

Preferred qualifications

• Experience in fast-paced or growth environments delivering data solutions under shifting priorities and timelines.
• Background enabling BI and data science teams via scalable integrations, data marts, and documentation that supports multi-tenant reporting or advanced analytics.
• Familiarity with batch and event-driven paradigms, including near-real-time pipelines using Snowflake, dbt, and Python.
• Experience automating operational, financial, or compliance-driven workflows in cloud data environments.
• Exposure to audit, privacy, and compliance frameworks (e.g., SOC, HIPAA, GDPR, ISO, SOX) and role-based access controls in regulated or healthtech contexts.

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 $104,000.00 - $130,000.00. 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: securityreporting@get-carrot.com