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# Sr. Data Engineer

- **Company:** Root, Inc.
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Salary:** $145,000.0 - $165,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Airflow, Amazon Web Services, Amazon S3, Data Analysis, JIRA, Audit Trail, Big Data, Software as a Service, Cloud Database, Code Review, Data Governance, Extract Transform Load (ETL), Github, Python (Programming Language), Data Streaming, Value Engineering, Workflow Management Systems, Google Cloud, File Transfer Protocol (FTP), Sql Optimization, Snowflake, Database Optimization, Backend, Git, Data Management, Software Version Control, Data Pipelines
- **Published:** October 27, 2026
- **Apply:** https://www.careerbuilder.com/job-details/sr-data-engineer-new-york-ny--f74c6fc2-ad49-4aa2-9b3e-a5906704750a

## About the Role

Cost Control, Health Plan, Clinical Practices/Protocols, Startup, Economics, Healthcare, Business News, Business Intelligence, Data Management, Data Quality, 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

## Description

* 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